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43
VIII/1/2017
INTERDISCIPLINARIA ARCHAEOLOGICA
NATURAL SCIENCES IN ARCHAEOLOGY
homepage: http://www.iansa.eu
Pedogenesis, Pedochemistry and the Functional Structure of the
Waldhufendorf Field System of the Deserted Medieval Village Spindelbach,
the Czech Republic
Jan Horák
a,b*
, Tomáš Klír
a
a
Institute of Archaeology, Faculty of Arts, Charles University, Celetná 20, 116 36 Prague 1, Czech Republic
b
Department of Ecology, Faculty of Environmental Sciences, Czech University of Life Sciences, Kamýcká 129, 165 21 Prague 6 – Suchdol, Czech Republic
1. Introduction
Agricultural feld systems have been heavily studied in the
central European area (
e.g.
Klír 2008; 2016; Kötschke 1953;
Krenzlin 1952; Krüger 1967; Lienau, Uhlig 1978). The
main points of these studies were the villages identifcation
and mapping in their terrain and the classifcation of the
villages based on their feld systems. Other studies have been
performed in Britain and elsewhere, generally in the north-
western and northern parts of Europe (Frandsen 1983; Hall
2014; Christie, Stamper, Eds. 2012). These feld systems
bear crucial information: not only about the agricultural
practice of rural societies, but also about the fundamental
agrarian, social, and environmental changes in Europe over
the last millennium (Hofmann 2014; Klír 2010a; 2010b;
Schreg 2013). That is to say, in European agrarian society,
feld systems have refected the socio-economic organisation
– and every feld pattern has been intrinsically connected
with the specifc economic and social relations, as well as
the agricultural practice (Hopcroft 1999, 15; De Moor
et al.
2002; Thoen 2004). The spatial distribution of agricultural
activities can also provide information about the “pure
culture” (Jones 2009).
The relationship between human settlement activities and
the soil part of the biosphere has been intensively studied
over the decades. Such intense study has introduced a wide
spectrum of topics: the infuence of soils on the placement
of human activities in the landscape; the interaction between
human activities and their soils; soils as one of the basic
archives of archaeological evidence; and also the role of
human activity as a factor in the pedogenic direction (Bork
et al.
1998; Walkington 2010). Nevertheless, there are
also stimuli for more multi-disciplinary research, as many
projects are still focused on either the historical or natural
perspective, without bringing them together. For example,
Rainer Schreg writes about the need to use an ecological
Volume VIII ● Issue 1/2017 ● Pages 43–57
*Corresponding author. E-mail: jan_horak@email.cz
ARTICLE INFO
Article history:
Received: 15
th
December 2016
Accepted: 5
th
May 2017
DOI: http://dx.doi.org/ 10.24916/iansa.2017.1.4
Key words:
Medieval colonisation
Medieval-Modern Era transition
village economy
feld system ecology
podzol
multi-element analysis
phosphorus
ABSTRACT
Spindelbach was a Waldhufendorf type of village,
i.e.
every household could manage its own felds
independently of other households. Our study has importance for research on the economic and social
development between the Medieval and Modern Era and for studies of human impact. Performing
soil and geochemical mapping, we have identifed four geochemical factors in a clearly interpretable
pattern: 1) general geology and soil environment (represented mainly by Al, Si, K, Ti, Rb, Sr and
Zr) contrasting with the soil organic matter and with pollution coming from atmospheric deposition
(P, As, Pb and LE – elements from H to Na); 2) modern pollution and possible historical human
activity (mainly As and Pb vs Zn, Fe and Mn); 3) historical human activity related to the village
(Zn and Sr); and 4) additional historical human activity of another spatial pattern (P). Although there
was no unambiguous relation between podzolization and the human activities observed, generally
podzol development was very rapid (it was positively observed on sites ploughed ca 600 years ago).
Diferences among the households’ agricultural managements were observed; these could be based on:
1) types of land use in the village area; 2) management intensity; and 3) the subjective management
preferences of the peasants. The diferences were manifested by their intensity and by their spatial
distribution.
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Jan Horák, Tomáš Klír: Pedogenesis, Pedochemistry and the Functional Structure of the Waldhufendorf Field System of the Deserted Medieval Village Spindelbach,
the Czech Republic
44
approach in landscape archaeology, where traditional
approaches usually only aim at the reconstruction of the
environment (Schreg 2014). We see the question from the
other side: an insufcient integration of archaeological and
palaeoenvironmental methods with purely historic themes,
as well as with historical periods (at least in the central-
European context where environmental archaeology prevails
in the research of prehistoric times).
Soils on archaeological sites are studied in many ways:
macroscopically (Kristiansen 2001), micromorphologically,
and geochemically. Some studies are focused on using
phosphorus (see Holliday, Gartner 2007), and there are
also studies using multi-element analyses. These analyses
are mostly focused on the diferentiation among basic
archaeological features (houses, felds, hearths and so on), on
the verifcation of human activities, and also on the analysis
of the spatial distribution of these activities (Davidson
et al.
2007; Nielsen, Kristiansen 2014; Roos, Nolan 2012;
Wilson
et al.
2009). The spatial extent of particular activities
(
e.g.
manuring) or land-use types (arable felds, pastures,
meadows, or gardens) has also been studied (Entwistle
et al.
1998; 2000; Salisbury 2013).
Our research of Spindelbach is part of a series of projects
focused on the medieval settlement and its transition into the
Modern Era (summary by Klír 2010a; 2010b). Thematically,
it belongs to the interest of European archaeology in the
Medieval-Modern Era transition and the processes of social
structure development, regional diversity, and economic
history (Andersson
et al.
2007; Cerman 2002; Cerman,
Maur 2000; Petráň 1964; Scholkmann
et al.
2009). The
archaeological context of the Czech research into the
Medieval settlement is relatively rich (Klír 2008; Krajíc
1983; Nováček 1995; Smetánka 1988; Smetánka, Klápště
1981; Smetánka
et al.
1979; Vařeka
et al.
2006). However,
the majority of this research has avoided mountainous areas,
where a combination of traditional agricultural subsistence
with non-agricultural production took place (Klír 2010a;
2010b).
We have chosen the village of Spindelbach for the
following reasons: 1) its location in a mountainous area (on
a ridge); 2) the preservation of at least part of its feld system
terraces, enabling the identifcation of felds belonging to
particular households; 3) it being a Waldhufendorf type of
village,
i.e.
an economic system where every household
could manage its felds completely independently of other
households; 4) the presence of other historical activities
unrelated to the village, but possibly infuencing geochemical
and soil conditions – charcoal-burning sites and glassworks;
5) the possible presence of non-agrarian activities – iron
processing – revealed by a previous reconnaissance of the
site; and 6) previously-observed podzolization gradients
enabling the study of its relation to human activities.
Our aims were: 1) to perform detailed soil and
geochemical mapping with respect to property ownership; 2)
to identify geochemical tracers (
i.e.
geochemical bearers of
information) of past human activity (
e.g.
phosphorus is the
tracer mostly used); 3) to perform analyses and assess the
spatial distribution of these tracers; 4) to evaluate possible
diferences among parcel strips (
i.e.
householder ownership)
and also within the parcel strips, and thus fnd possible
management intensities and attitudes among householders;
and 5) to fnd and identify the possible relation between
podzolization and human activity.
2. Materials and methods
2.1 Study site
The deserted Medieval village Spindelbach was located on
a ridge of the Krušné Hory (Ore Mountains, Erzgebirge)
in north-western Bohemia, ca 3 km NW from the small
town of Výsluní, close to the Czech / German border
(50°28
′
52.995
″
N, 13°11
′
42.143
″
E) – see Figure 1.
The site (Figure 2 and Figure 2.1 in Supplementary
Online Material – SOM) consists of a built-up area along
the Prunéřovský stream (originally called Spindelbach) and
the felds coming from it in the form of parcel strips aligned
in a south-west to north-east direction (research into which
is presented in this study). The main system of probes and
places in the area of the researched feld system is based on the
system of parcel strips numbered upwards with altitude, and
distance, meaning the distance from households (since the
main feld pattern is a linear one from households). The term
“distance” always means the distance from the households
in the direction of the strips – in the text, on plots, in fgures
and in tables. The terms used for spatial descriptions are
also related to distance from households: “village vicinity”
being the area of felds up to a distance of ca 350 m, and
the term “distant part” marks the area of felds between a
distance of 950 to 1750 m. The “background area” marks the
area around the background probes 100001 to 100005. The
term “high altitude area” means the area above the last (13
th
)
strip, which includes the background area. There are also
other historical landscape features such as: charcoal burning
sites (almost all over the researched area up to the distance of
750 m); agrarian stone heaps/mounds found only in the area
of strips no. 8 to 12 to the maximum distance of 350 m; and
glassworks (built-up area at the altitude of strip no. 10 and at
Figure 1.
Location of the study area in the Czech Republic near the
Czech-German border. Grey areas indicate the spatial distribution of
“Waldhufendorf” feld system type in central Europe (by Schröder, Schwarz
1969: map “Die ländlichen Ortsformen in Mitteleuropa gegen Ende des
Mittelalters”).
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Jan Horák, Tomáš Klír: Pedogenesis, Pedochemistry and the Functional Structure of the Waldhufendorf Field System of the Deserted Medieval Village Spindelbach,
the Czech Republic
45
strip no. 4, at the distance of 750 m). There were 13 parcel
strips identifed, mainly on the basis of LIDAR data and
feldwork observation. There was a place for one or two
possible parcel strips more, but it was impossible to decide
their possible presence clearly due to the lack of any terrain
marks or LIDAR data (the terrain there was merely fat). At
higher altitudes, it was mainly peat bog terrain and thus we
did not presume any parcel strips there.
2.2 History of the village
The village came into existence in the 13
th
century (probably
in the second half, see Crkal, Černá 2009). There were also
three glassworks in the area chronologically preceding the
village’s existence with no clear functional connection to
the village; there was probably some chronological hiatus
between them. There are toponyms like “Glassberg” in
Medieval-written sources, but with no notes about the
glassworks themselves. It is therefore probable that the
glassworks were abandoned by the time of the village’s
foundation (Crkal, Černá 2009). The glassworks were located
in the area of later village felds (strip 4, distance 750 m)
and in the built up area at the altitude of strip 10 (Figure 2
and Figure 2.1 in SOM). There was also a third glassworks
in the south-western part of the village vicinity. The frst
written record concerning the village comes from 1356
(RBM VI, 175 No. 329; written as “Spinnelbach”), when it
belonged to the Alamsdorf family. The last written source
comes from 1481, when half of the village was sold (Profous
1951, 552; Sedláček 1923, 59). The Hasištejn dominion
property, to which Spindelbach belonged at that time, was
divided in 1490 and there was a note about Spindelbach in
the division document, but only of Spindelbach as a forest
and a fshpond, not a village (AČ V, 543). Therefore, it is
presumed that the village had been abandoned sometime
between 1481 and 1490. The toponym “Spindelbach” and its
variants marking forests, fshponds, or meadows, were noted
in written sources from the 16
th
and 17
th
centuries; it can also
be found on the frst military mapping of the area from 1767,
or on the stabile cadastre map from 1842 (Crkal, Černá 2009;
Figures 13.6.1 to 13.6.5 in SOM).
Spindelbach was a typical “Waldhufendorf” (or
“Gelängefur” –
e.g.
Klír 2008, 158) village. We base this
statement on these indications: 1) it was a typical village
system in this region; 2) the preserved parcel strips system
in the form of terraces was fairly regular and the strips were
spatially connected to the individual households; and 3) our
team is experienced in researching such villages and their
feld systems (
e.g.
Klír 2008; 2010a; 2010b; 2013; Klír,
Kenzler 2009). Waldhufendorf was a regular feld system in
central Europe, which was developed during the reclamation
of woodland along middle to high altitude mountains during
the High Middle Ages,
i.e.
from the 11
th
to the 14
th
century
(Krüger 1967; see Figure 1 – grey areas). This feld system
consisted of wide, long strips, almost equal in size to that
of each farmstead, ideally ca 100 m×2300 m (Kuhn 1973;
Krüger 1967, 109–110; see Figure 3). Spindelbach parcel
strips were only about 50 to 55 m wide. The peasant
farmstead lay at the head of the strip. Slightly curved, the
strips were adapted to the topography. It is important to
mention that the agrarian system was individualistic rather
than communal. This means that each farmstead could
make its own economic decisions regarding their cultivation
independently, because each strip was easily accessible as a
consequence of its compact position within the landholding
(Lienau, Uhlig 1978, 216; Krüger 1967; Hopcroft 1999,
22–24). In the Modern Period, the original feld pattern was
usually disrupted and the strips subdivided as a consequence
of socio-economic diferentiation (
e.g.
Born 1977, 167–170).
Figure 2.
The examined part of the feld
system. The Prunéřovský stream is located
in the built-up area at the left edge of the
fgure. Houses are located only along
this stream. The depicted altitude ranges
between ca 800 and 915 m above sea level.
The probes in felds are marked by crosses,
the background probes are located in the
highest areas and are marked by stars and by
numbers 100001 to 100005. Agrarian stone
heaps are located mainly in the western
corner of the studied area (ca strips 8 to
12, distances 50 to 350 m). Glassworks are
located in the built-up area (against strip 10)
and in the felds (strip 4, distance 750 m).
For a colour version, see Figure 2.1 in SOM.
0 2000 m
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2.3 Environment
The village was located on a gentle southern slope, just
under a ridge of the Ore Mountains, at an altitude of ca 700
to 900 m asl (researched area ca 800 to 900 m asl). The
built-up area was situated along a little stream (Prunéřovský
potok) – see Figure 2. The average annual air temperature
is between 4 and 6°C, and the average annual sum of
precipitation is between 800 and 1000 mm (Tolasz
et al.
2007). The geological bedrock is mostly made of Palaeozoic
and Proterozoic orthogneisses and paragneisses (Figure 13.2
in SOM). In the surroundings of water streams, thick fuvial
and colluvial sediments of weathered material can be found.
The soil cover appears to be made of cambic podzols
(according to Czech map sources – see Figure 13.4 in SOM),
which corresponds to haplic podzols by the World Reference
Base for Soil Resources taxonomy (WRB), or to spodosols
by the US Soil Taxonomy (USDA). This soil appears to
be distributed homogeneously over the whole study area.
Only the fat, highest areas with peat bogs are covered by
organic soils – histosols. Our detailed sampling enabled the
observation of gradients of soil types between cambisols to
podzols (cambisols to haplic and entic podzols by WRB, or
inceptisols to spodosols by USDA). Cambisols are the soils
characterised mainly by intrasoil weathering reaching into
the yellowish, reddish and brownish B horizon. Sometimes,
this B horizon can be more coloured in its upper part (higher
chroma in Munsell system). Podzols are soils originating
mainly in mountainous regions with a humid climate,
coniferous vegetation cover, and an acid pH, leading to the
leaching of clay minerals, organic matter, cations, and so on
downward through the profle. As a result, a greyish to white
“eluvial” E horizon can be observed beneath the organic-
mineral A horizon. The transported matter is accumulated in
the B horizon, leading to its stronger colouring in reddish
and brownish colours. The schematic sequence of the
horizons can be seen in Table 1, and examples of the studied
Figure 3.
A typical feld system of
Waldhufendorf: Röllingshain (Saxony,
Germany, by Kötschke 1953: Figure 27).
Note boundaries between households and
their parcel strips. Every household has its
own parcel strip, which can be managed
independently of other parcel strips. The
picture displays usual the pattern of land-
use types: felds and forests at the ends of
parcels. Such detailed ground plans are
available only for villages still existing in
Modern Era mapping, and not for villages
abandoned in the Medieval Era.
Table 1.
Schematic description of soil horizons and their labels used in this study. Table features: * O, A, E, B and C are used among majority of description
systems, though detailed descriptions can vary; ** these labels are used only in this study for purposes of statistical analyses and visualisation, BD stands
for B Darker facies; *** data from these horizons are not presented in the paper; cm represents where the horizon was measured: A and E in every 1
st
and 3
rd
cm of that horizon, BD and B30 in every 2
nd
and 7
th
cm; also depths 30 and 40 cm were measured irrespectively of the horizon; † measured irregularly only
in few cases; See also fgures 13.5.1 to 13.5.8. in SOM.
Cambisols*Podzols*Labels Used**cmDescription
OO
***0
Organic, not fully decomposed matter on the surface
AAA1., 3.Dark, almost black organic-mineral horizon
no E
E***1., 3.Eluvial, grey to white horizon, leaching zone
BBBD2., 7.Darker facies of B horizon, accumulation zone
BBB302., 7., 30B horizon, also accumulation zone, to 30 cm
BBB31–4040B horizon in depths 31 to 40 cm
BB***†B horizon deeper than 40 cm
CC***†C horizon – weathered bedrock, parent substrate
0 500 m
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profles, including horizon descriptions, can also be seen in
Figures 13.5.1 to 13.5.8 in SOM. The soil matter was made
mainly of silt and sand material. Gravel-like and stone material
could be found mainly at depths of 40 cm and deeper. It was
also observed at depths of around 20 cm in strips no. 10 and 12.
We have also found large boulders in the probes, but only in a
few cases (strip no. 12, at distances of 150 and 550 m, and strip
no. 4, at 750 m). We have usually found the transition between
the B and C horizons to be at depths around 50 to 60 cm; no
frm bedrock was found in the probes. We have found varieties
of soil types on a gradient going from cambisols to podzols. As
a basic deterministic characteristic of the position of the soil
on this gradient, we used the distinguishing of the presence of
the E horizon, with the possibilities: “no”
i.e.
the soil type was
cambisol; “yes”
i.e.
the soil type was a podzol; and “juvenile”
– there was observed some slight indication of eluviation –
juvenile stages of E horizon. The schematic mapping of the
distribution of these categories is presented in Figure 4. From
a comparison of Figure 4 and an output from the ofcial Czech
pedological mapping (Figure 13.4 in SOM), it can be seen that
merely mapping is unsuitable for any detailed archaeological
work and interpretation. We also performed an interpolation
of thickness of the E horizon, which could be used as proxy
information for the rate of podzolization (see Figure 4.1 in
SOM).
The hydrology is represented by numerous streams, three
of which are permanent in character: 1) the Prunéřovský
stream in the built up area; 2) unnamed streams at distances
of 550 to 750 m; 3) a stream along the probes at a distance of
950 m. Other streams of the researched feld system area are
intermittent in character. There are peat bogs at the highest
altitudes in an area behind the ridge (along the upper edge
of Figure 2).
2.4 After desertion – land use, land cover, pollution and
modern forest management
It was mentioned that the toponym Spindelbach was related
mainly to the forests and meadows after the village desertion.
The name was also related to the stream (Figures 13.6.1. to
13.6.5 in SOM). The meadows were located only in the area
of the previously built-up area, and the village felds were
covered by forests. Sometime in the course of the Modern
Era, there was some charcoal burning activity performed in
the area (see location of charcoal burning sites in Figure 2
and in Figure 2.1 in SOM). This activity probably did not
chronologically relate to the village existence due to its
collision with the village agriculture. There were also
probably unusable forests during the time of the village. We
interpret this activity as related to mining and ore processing,
which started in this area during the 16
th
century (the town
Výsluní was originally a mining town). Modern forest
management focuses on the growing of spruce (
Picea sp.
) and
larch (
Larix sp.
); birch trees (
Betula sp.
) can also be found
in the area. During the 1970s and 1980s, there was important
ecological damage made to the Ore Mountains vegetation as
a result of acid SO
x
and NO
x
rains (chemicals coming from
the industrial area in north-western Bohemia). This was
followed by an invasive action of forest management, based
on bulldozering the soils into mounds (after damaged timber
mining) and on the spreading out of these mounds several
years later. This action damaged and mixed the original soil
profles. The areas managed in this way can be found in the
south-western parts of the village feld system, in the highest
areas, and also in the study area at the distances of 1150 to
1750 m. The character of the forest land cover can be seen
in Figure 13.3 in SOM. For an example of land cover types,
see photos in Figures 13.7.1, 13.7.2 and 13.7.3 in SOM.
Figure 4.
The scheme represents the
observed presence of podzolization in all
probes to visualize the heterogeneity of
soils in the study area. It also shows the
sampling pattern / grid in its ideal form.
Note three lines of sampling at distances 50
to 750 m. Grey rectangles indicate probes
where no E horizon (
i.e.
macroscopically-
manifested podzolization) was observed.
White rectangles indicate the presence
of E horizon. For another visualization
(E horizon thickness) see Figure 4.1 in SOM.
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The usual planting of young plants does not damage the soil
profles substantially.
2.5 Research history
In 2006, Jiří Crkal found shards of medieval pottery and of a
glassmaking pan in the area of one of the forest management
earth mounds. During subsequent exploration, the remnants
of houses were found. Over the following years, non-
destructive research of the glassworks was performed
(Crkal, Černá 2009). Metal detector exploration of the
built-up area was also performed. It brought an indication
of possible iron processing in the village area (Hylmarová
et al.
2013). There was also some collection of pottery shards
on the mechanically-levelled areas and mounds, performed
mainly in the southern and south-western parts of the village
area. There was observed an interesting threshold between
areas with and without stones (indicating a cleared arable
area) on one of these levelled areas. It was at a distance
of ca 850 m in the area we would parcel number as 0 (our
numbering system; pers. comm. Jiří Crkal). Research
activity from 2010 to 2015 focused on the excavation of
one of the households, geodetic measuring of the village
terrain remnants, and LIDAR scanning of the area. These
excavations and researches have only partly been published
up to now. Two smaller researches were performed in the
area of the felds: sampling for measuring δ
15
N values in
2011 (Součková
et al.
2013) and excavation of the terrace
steps (strip no. 8, distance 50 m: two probes of 10×1×0.4 m)
in 2013. Shards were observed to a depth of 40 cm, but no
traces of ploughing were seen in the soil profles. In 2014,
probing and sampling was performed in strips no. 2 to 12
at distances from 50 to 750 m and, in 2015, probing and
sampling from 950 to 1750 m and background probes were
undertaken.
2.6 Research design
Soil sampling was based on a regular grid of strips and
distances; sampling was only performed in even numbered-
strips. In the season 2014, we sampled distances 50, 150,
350, 550 and 750 m and in season 2015, at 950, 1150, 1350,
1550 and 1750 m, as well as fve background probes. To
assess soil mosaic diversity, we sampled every strip in the
2014 season (from 50 m to 750 m) in three lines named in
accordance to their position on the slope within the strip:
“higher”, “middle” and “lower”, three probes thus being
sampled in each strip (for the distance combination in this
part of the study area, see also sampling pattern in Figure 4).
Strip borders were identifed by LIDAR scanning and,
in some cases, also by terrain observation. At distances
from 950 to 1750 m (season 2015) only the “middle” line
was sampled, the reason being the impossibility of safely
identifying strip borders due to changes in the surface
characteristics because of the forest management. In these
parts of the feld system, we therefore sampled the probes
in a strip-like pattern based on 200 m steps on an azimuth
based on the directions between probes at the 50 and 750 m
distances. Only the probes at the 950 m distance were placed
according to the direction between the probes at the 550 and
750 m distances. Probes were sometimes placed out of the
ideal grid; the usual reasons for repositioning probes were
trees, forest management ways, and forest-management
soil profles being damaged by mechanical levelling at
distances 950 to 1750 m. Distances of repositioned probes
from their ideal location were always less than 10 m. It
was possible to place probes in a preserved soil profle in
damaged areas where old forest areas or old trees groups
had also been preserved. This can be seen in Figure 13.3
in SOM, for example, at distances 1350 m or 1550 m (old
forest represented by dark green vegetation cover). Only in
the case of probe no. 1035 (strip no. 10, distance 1150 m)
we were unable to fnd any suitable place (the probe was
sampled, but the data was not processed in the analyses). We
made 120 probes in the felds and 5 probes for “background”
values. We included background probing and analyses to
reveal possible relationships of the felds’ geochemistry to
the presumably uninfuenced environment. Since it was not
possible to fnd an area comparable to the felds that was
defnitely uninfuenced by past human activities (it was not
clear if there were other parcel strips next to parcel strip 13),
we still tried to sample in areas distant from the village,
at least for comparing soil, geology and vegetation. We
therefore tried to avoid sampling in peat bogs, and in areas
of unstable soil where trees tend to uproot: both of these
environments covered most of the area outside of the felds.
Indeed, the background probe sites were the only possible
places.
It should be noted that the felds-background relationship
was only secondary, as we primarily aimed at intra-feld
spatial diversity. We saw the amount from 120 feld probes
as sufcient for obtaining the “intra-feld” context and
diversity; in addition, we saw the background probes as
unnecessary for this primary task. This was also one reason
for not placing the probes right in the built-up area (besides
which, we did not want to disturb the archaeological features
there). However, we saw both these relationships (to the
background and to the built-up area) as worthy of study in
some separate future research.
The size of probes was ca 40×50 cm to 50 cm depth. Their
profles were photographed and described. Since we wanted
to compare data across the whole area, we divided horizons
into these basic categories (see Table 1 and Figures 13.5.1.
to 13.5.8 in SOM): “A” horizon; “E” horizon; and “BD”
horizon (which stands for B darker –
i.e.
darker facies in
upper part of the B horizon). As the B horizon itself was
usually several dm thick, we divided it into mechanical
layers. The “B30” marked that part of the B horizon between
the “BD” horizon and a depth of 30 cm, the following “B31–
40” marked depths 31 to 40 cm; for information about the
measured depths, see Table 1. Every depth was measured
three times; in the case of diferent or unusual values, two
additional measurements were performed. We also took
samples of soil material at a 20 cm depth for potential
future analyses. However, the main way of obtaining data
was direct feld-profle measurement by means of a portable
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ED-XRF (PXRF) analyser Delta Professional, by Olympus
InnovX, used in Soil Geochem measurement mode (for
applications of XRF spectrometry, see Canti, Huisman 2015;
Hürkamp
et al.
2009; Kalnicky, Singhvi 2001; Šmejda
et al.
2017). It should be stated that this method obtains values of
almost the total concentrations of elements in the sediment,
as opposed to the usually used methods working mainly with
near organic-available fractions. But some studies have used
near total concentrations successfully (Entwistle
et al.
1998;
2000; Wilson
et al.
2005). During taking measurements, we
avoided those places whose profle contained parts with only
a coarse fraction (above 2 mm) present (it was only in a few
cases at depths of ca 40 cm or deeper). All measurements
were performed for time for one minute, with 30 s of the
10 kV beam and 30 s of the 40 kV beam. The PXRF model
used gives data in the form of weight ppm. The quality of
the device’s measurements was successfully tested by BAS
Rudice Ltd. (www.bas.cz) on 55 reference materials (
e.g.
SRM 2709a, 2710a, 2711a, OREAS 161, 164, 166, RTC
405, 408).
2.7 Statistical and GIS analyses
The basic input data for all the analyses was computed as
an arithmetic mean for every probe and horizon. The data
matrix originating from this process can be seen in SOM, fle
“Tables”, where the data is presented as a whole, and also
as data fltered to A, E, BD, B30 and B31–40 horizons. For
further analyses we used only these elements: Al, Si, P, K, Ti,
Mn, Fe, Zn, As, Rb, Sr, Zr, Pb, LE (light elements – H to Na
concentrations lumped together due to the principles of the
PXRF method used) which reached at least 505 cases (due
to the detection limits not all elements were measured in all
cases). The basic matrix therefore consisted of 14 variables
and 505 cases. In none of the analyses did we work with
the original concentration values. Geochemical data can
be generally characterised as (usually) of a non-normal
distribution (Limpert
et al.
2001; Reimann, Filzmoser
2000) and as compositional data (Reimann
et al.
2008;
Reimann
et al.
2012). According to Reimann
et al.
2008, we
therefore decided to preferably use clr-transformed data. The
abbreviation “clr” stands for centred log-ratio: the data was
divided by the geometric mean of their data point and then the
values were log10 transformed. This process helps to avoid
some of the problems with compositional data, where the
variable cannot reach any value, but is limited by the values
of the other variables (Reimann
et al.
2008). This process
enables the use of additional information in the data matrix
(for visualization of this process see Figure 11 in SOM).
We used principle component analysis (PCA) as a basic
processing method: not only for making the interpretation
easier, but also for distinguishing between the possibly
diferent inputs of elements into the soil environment. As
the input data for PCA we used the whole matrix. We used
Statistica 12 software for PCA. For spatial visualization, we
used GIS interpolation (ArcGIS 10.1, Geostatistical wizard
tool and the kriging interpolation method). We interpolated the
principal components (PCs). An interpolation was performed
for the data from the A, BD, B30 and B31–40 horizons, the
majority of the data being in these horizons. For visualization,
we used one continuous colour scale for all four horizons.
We also wanted to utilize the information about the parcels
themselves and also visualize the data for only those areas
for which we had data (
i.e.
the even numbered parcel strips
and background area). Therefore, we also used a difusion
kernel for interpolations of those PCs which we interpreted
as human related, since it enables the use of barrier features
in the interpolation process – in our case, we used the
parcel strip borders as such barriers. As we are aware that
phosphorus is an almost certain human activity tracer, we
have also presented interpolations of its concentration to
enable a comparison with the clr-transformation process
(Figures 26.1 to 26.4 in SOM). Since we wanted to assess
if there were any diferences between the strips (manifested
by diference in elements / PCA components – and possibly
interpreted as human activity tracers) we performed an
ANOVA of the human-interpreted PC coordinates from the
BD and B30 horizons together. We performed an ANOVA
among the strips for every distance separately, and also an
ANOVA among the distances for all strips separately. For a
visualization of this, we used the results of a post-hoc Tukey
test for diferences using R, version 3.1.2 (2014-10-31) –
„Pumpkin Helmet“ Copyright (C) 2014 The R Foundation
for Statistical Computing (R Core Team 2014).
3. Results
3.1 Macroscopic observations
Out of 125 probes in total, we have found podzols in
49 cases, cambisols in 65 cases, and 11 cases of juvenile
podzolization. As presented in Figure 4 (and in Figure 4.1 in
SOM), cambisols were more spatially related to the village.
There can be two gradients seen in the part between distances
50 and 750 m. The frst gradient was along the distance,
the second gradient along the altitude. However, the part
of the felds between 950 and 1750 m did not correspond
with either of these gradients. There was no clear gradient
/ pattern interpretable as being related to human activities.
We did not observe any other features in the soil profles,
such as traces of ploughing and so on. The Figures 13.5.1 to
13.5.8 are good representatives of soil profle appearances in
the area of the felds. We have found pottery shards in some
probes: strips 2 and 6, distance 50 m, and strip 4 at distances
50 and 350 m.
3.2 PCA results
PCA extracted 13 components (marked PC 1 to PC 13,
see Table 2 for simplifed results; and SOM, fle “Tables”,
for complete results). All analysed elements were strongly
connected to the frst two PCs. Although only the frst four PCs
reached an eigenvalue greater than 1, the spatial distribution
of PCs enabled those PCs with lesser eigenvalues to also be
interpreted: especially PC 4 and PC 7. For visualizations of
the interpolation, please see Figures 5 to 8 (chosen PCs and
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50
Table 2.
Variables loadings of nine principal components. PCA results: loadings of variables. Only values ≤–0.25 and ≥0.25 are depicted, values ≤–0.7 and
≥0.7 marked in bold. All data including components 10 to 13 can be seen in SOM, PCA eigenvalues and PCA loadings.
PC 1PC 2PC 3PC 4PC 5PC 6PC 7PC 8PC 9
Al 0.65–0.46–0.28 0.49
Si 0.63–0.67
P
–0.73
–0.46 0.4
K
0.88
–0.31
Ti
0.91
Mn 0.32
0.84
–0.26 0.31
Fe
0.79
0.34 0.41
Zn
0.74
–0.41 0.28
As
–0.70
–0.57 0.40
Rb
0.86
–0.31
Sr
0.76
0.44–0.25 0.26
Zr
0.85
–0.31
Pb
–0.82
–0.5
LE–0.60–0.60–0.30 0.28
Eigenvalue 6.53 3.09 1.15 0.95 0.66 0.47 0.37 0.24 0.23
Cumulative %46.7068.7476.9883.7388.4491.8294.4896.2297.86
Figure 5.
Kernel interpolation of PC 4 in the BD soil horizon. See colour
versions in Figures 20.2 and 21.2 in SOM.
Figure 6.
Kernel interpolation of PC 4 in the B30 soil horizon. See colour
versions in Figures 20.3 and 21.3 in SOM.
Figure 7.
Kernel interpolation of PC 7 in the BD soil horizon. See colour
versions in Figures 24.2 and 25.2 in SOM.
Figure 8.
Kernel interpolation of PC 7 in the B30 soil horizon. See colour
versions in Figures 24.3 and 25.3 in SOM.
0 2000 m
0 2000 m
0 2000 m
0 2000 m
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horizons) and also Figures 17.1 to 25.4 in SOM (coloured
versions for PC 1 to PC 7 in all soil horizons). For PCs` relation
to altitude, depth and distance, see Figures 16.1 to 16.3 in SOM,
and for relation to podzols see Figure 15.2 in SOM.
PC 1 was positively connected to geogenic elements,
such as Ti, Rb, Sr, Zr, Al and Si, and negatively to P, As,
Pb and LE. Its values were manifested mainly in the
vertical dimension: the manifestation of negative values
being in the A horizon and positive values oppositely in the
B31–40 horizon. There was no clear connection to altitude;
yet there was a visible relation to depth and a very subtle
relation to distance from the village (negative values were
manifested more in proximity to the village). There was also
no diference in the values between sites with and without
podzol E horizon. PC 2 was connected mainly to Mn, Fe
and Zn, and negatively to Si, As and Pb. A clear vertical
gradient was also found: positively connected elements were
manifested mainly in the B31–40 horizon, and furthermore
Figure 9.
Visualization of the Post-hoc Tukey test: diferences among strips. Segments indicate pairs of sites with statistically-signifcant diferences.
Figure 10.
Visualization of the Post-hoc Tukey test: diferences among distances. Segments indicate pairs of sites with statistically-signifcant diferences.
Only pairs of sites of mutual distance under 400 m presented. For all diferences see Figure 10.1 in SOM.
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in the vicinity of the village. A slight relation to altitude, depth
and distance was also observed. PC 3 was connected to Al,
Zn and LE (negatively), and to Fe and As (positively). For
PC3, no clear patterns were found in the spatial distribution.
PC 4 was related to Zn and Sr (positively), and to Al, P and
Rb (negatively). A clear spatial relation of positive values to
the village was observed in all soil horizons; there was also a
clear decreasing pattern along the distance gradient. PC 5 was
related mainly to Al and Sr; no clear pattern was found. We
have also found no clear pattern in the case of PC 6 related
to Fe, LE and Mn. PC 7 was positively related to P. This PC
was spatially manifested mainly in the village vicinity in all
soil horizons; there was also a decreasing pattern along the
distance gradient. PCs 8 and 9 were of no clear pattern.
3.3 ANOVA
Since we presume PCs 4 and 7 to be the tracers of human
activity, we performed an ANOVA on them. The results of
the post-hoc Tukey test can be seen in Figures 9 and 10.
Clearly, there were more diferences among the distances
than among the strips. PC 4 recorded more diversity than
PC 7. The diversity among strips was based mainly on the
presence of one separate strip that was diferent from all
other strips.
4. Discussion
4.1 PCA
We interpreted PCs 1, 2, 4 and 7. Other PCs were not so
clearly interpretable. PC 1 was a representation of a contrast
between the natural, geogenic part of the local geochemistry,
and the anthropogenic inputs. The natural part represented
by geogenic elements was manifested mainly in deeper
horizons. Anthropogenic inputs were manifested mainly in
the topsoil A horizon, suggesting an origin for the As and Pb
in the atmospheric deposition, probably originally coming
from man-made pollution. LE (and probably P too) in PC 1
represent the organic matter in the topsoil. PC 2 has been
interpreted as a representation of two probably-anthropogenic
inputs: As and Pb again representing pollution from the
atmospheric deposition input; positively correlated Mn, Zn
and Fe probably representing historic anthropogenic input
from the medieval village. This interpretation was based
on the spatial relation of the positive values to the village
vicinity; these elements also tend to record anthropogenic
activities. Despite this interpretation, we have not used this
PC in other analyses due to the fact that the historic activity
was recorded mainly in the deepest horizon (B31–40). There
is also the question of the division of As and Pb into the frst
two PCs and the possible historic or ancient origin of at least
part of this pollution. Could the As and Pb be related to some
non-agrarian activity,
e.g.
iron processing in the village, or
generally to medieval or older mining or smelting activities
in the Ore Mountains? Such a possibility has been recently
presented (Veron
et al.
2014) for a peat bog profle from the
Ore Mountains by isotopic analyses.
PC 4 was interpreted as a representation of village activities
recorded in the input of the usually human-related elements
Zn and Sr. These were also spatially manifested mainly
in the village vicinity. The presence of P and its negative
correlation with PC 4 remained uninterpreted. Phosphorus
should be a candidate for a human activity tracer too, but
we did not found a clear interpretation of it for this PC; its
spatial distribution (see blue colours in Figures 20.1 to 20.4
and 21.1 to 21.4 in SOM) was clearly based on high values
of P concentrations (see Figures 26.1 to 26.4 in SOM). The
absolute values of P concentrations in the local geochemistry
clearly recorded diferent inputs than that of the medieval
village. The transformation and statistical procedures (PCA)
helped to improve the data structure: analysing only the
concentrations would not have been sufcient here. We have
also been able to obtain a separate record of human activities
recorded by P. It was from PC 7, related only to P and also
spatially related to the village vicinity. Besides that, distant
parts of the feld system were also manifested, though not so
heavily (see Figures 24.1 to 24.4 and 25.1 to 25.4 in SOM).
4.2 Relations to other features
We also tried to examine the relation of PCA results to the
features in the area, especially to charcoal burning sites,
glassworks, stone heaps, water streams and, of course, to the
podzol distribution. The relation to podzols was one of the
main aims of this study, since we presumed that its spatial
distribution has been infuenced by human activities in the
past (as was shown, for example, by Kristiansen 2001).
Surprisingly, the relationships of PCs to podzols were very
faint. We examined the ratios of PCs` case coordinates
between horizons (podzolization is generally characterized
by a downward transport of fne soil material, including ions,
organic matter, clay minerals and so on, based mainly on
acid pH and higher precipitation; therefore the ratio between
vertical levels should indicate such transport). The results
were visualized in the form of box plots (see Figure 15.2
in SOM). We also added the results of the same analytic
data processing of element concentrations for comparison.
The results were diferent: almost all elements recorded
diferences between “yes” and “no” podzols (Figure 15.1 in
SOM). However, the PCs recorded the diferences in only a
few cases: PC 4 recorded a diference between A and B30
horizons; PC 7 recorded no diference.
There were many places of charcoal burning. The spatial
distribution of the PCs mainly refected these sites in those cases
where the PC was related to Zn (PC 2 and 4). This was clearly
refected in site 823 (strip no. 8, distance 750 m), where the
probe was placed directly in a charcoal-burning hearth (values
of Zn here were higher than usual). Indications of a relationship
between these PCs and charcoal-burning sites were found, for
example,, in the case of PC 4 (BD horizon – see Figure 5, and
also Figure 20.2 in SOM). The spatial distribution of PC 4 could
be infuenced by the distribution of charcoal-burning sites –
both were placed mainly in the village vicinity.
Three probes were placed right in the area of glassworks
(studied by Crkal and Černá 2009) in strip no. 4, at a distance
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of 750 m. This site showed no distinctive values for any of
the PCs. Only PC 5 in the BD horizon (Figure 22.2 in SOM)
refected this area, but no clear relationship was observed in
other horizons. The spatial distribution of stone heaps was
bound to only a small part of the whole felds system: in the
western corner of the study area with no clear relation to
any of the geochemical characteristics. Water stream areas
were researched mainly in the central part of the felds
system, between distances of ca 550 to 950 m. It could be
seen on maps that this area had no substantial infuence on
the geochemical situation. Only in the case of PC 3 could
some weak relation be seen (BD horizon – Figure 19.2 in
SOM).
Interpretation of the background probes was also
interesting. The idea of a geochemical background is
complicated: there are many defnitions of it (see Reimann
and Garrett 2005). Archaeology, especially, should be aware
of the fact that – with its necessity of using of a long-term
view – the natural background has changed substantially
during prehistory and history. It is more a rhetorical question
than a real one: is there a natural geochemical background to
be found in such regions as those we deal with in Europe?
Our research in Spindelbach has found that the problem of
“background” can be really difcult to design and interpret.
The concentrations of phosphorus were highest in two of
the “background” probes. At this stage in our research, we
cannot interpret it clearly: it could be due to unknown human
activity placed there, or due to a diferent P input into the soil
unrelated to human activity. A decision would require further
research. Generally, the difculty of fnding an uninfuenced
background is the norm in regions of dense settlement. The
Spindelbach example has clearly shown that it could also be a
problem to fnd a background in extreme and marginal areas,
or, the design of “background” probes placement would have
to be based on diferent ideas to that of only “the background
can be found anywhere outside the human-infuenced area”.
An important result from the Spindelbach background
research was that it would be problematic to only work with
just concentrations: the possible “background” recorded the
highest levels of phosphorus concentrations. This should
be resolved by the research design or by using appropriate
analyses. In our case, this was resolved by using multivariate
statistics able to distinguish diferent element inputs.
Similarly, we could discuss a possible relation to the other
extreme of human activity – the built-up area. This would
probably not just mean extreme values of human infuence
recorded in the felds, but would be combined with other
human activities not refected in the geochemistry of the
felds. The relation of the felds’ geochemistry to both the
background and to the built-up area should be analysed
in separate future research (not focused primarily on the
felds as we have done) with a suitable design of sampling
(
e.g.
same numbers of probes in all categories, same or
similar pattern of placing of probes) and with a suitable
interpretational approach (
e.g.
dealing with a radically
diferent spatial diversity in all categories). It should be
noted that the geochemical record of human activities in the
built-up area was analysed in another research performed at
Spindelbach (record in alluvial sediments).
4.3 Ploughing
We have not found any traces of ploughing in the soil profles.
Possible reasons for this are: 1) the research design as we
performed it did not primarily focus on searching for these
traces; 2) in addition, the dimensions of the probes were
small (although we did not fnd any traces in larger probes
focused on the terrace steps performed in the 2013 season);
3) pedogenesis (mainly podzolization processes) have erased
possible traces and therefore the soil profle has changed
through the period since the village abandonment. Of course,
one could express an objection to this interpretation: maybe
there was no ploughing performed at all. But this possibility
should be treated as nearly impossible due to the following
reasons: 1) historical impossibility: even in villages producing
non-agricultural goods for trade, agricultural activities (that
included arable felds) were performed for the subsistence of
the villagers themselves; 2) the terrace system preserved in
Spindelbach was a clear evidence of ploughing, for terraces
were created by ploughing in order to make ploughing in
slope areas easier and to prevent soil erosion; 3) pottery
shards found at depths to 40 cm (in season 2013 probes);
4) pottery shards found in probes of 2014 season; 5) feld
clearing of stones found on one of the mechanically-levelled
areas at distance 800 m (pers. comm. Jiří Crkal). It should be
one of the tasks for future research at Spindelbach to focus
on soil traces and the micromorphology in more detail.
4.4 Diferences in land use and management
This was one of the main aims of this study: to fnd out if
there were spatial diferences in human activity tracers.
Some diferences and gradients could be seen. The spatial
distribution of the PCs 4 and 7 (Figures 5 to 8, and 20.1 to
21.4 and 24.1to 25.4 in SOM) has brought some information.
A major diference was observed between the village vicinity
and the distant parts of the feld system. The village vicinity
was related to the clear manifestation of both PC 4 and PC 7
(and also to PC 2 in B31–40 horizon) and we could interpret
this as more intensively-managed arable felds. The distant
part was only related to the weaker manifestation of PC 7.
We could interpret such patterns in this way: 1) intensively-
managed arable felds in the village vicinity; 2) arable felds
with weaker management in distant parts; 3) probably
pastures in the central part with the water streams. The
management of distant parts was also indicated by the fnding
of a whetstone (see Figure 12 in SOM) in strip 6, ca 1250 m
from the village. The management itself was diversifed by
two tracers of diferent inputs: 1) PC 4 with Zn and Sr; 2)
PC 7 with P. Thus PC 7 could easily be connected to the
manuring of arable felds. PC 4 could be seen as a tracer
of ash (Zn) or of household midden (Sr) input (references
hereafter). The spatial distribution restricted to the area of
the strips revealed some diferences: PC 4 and the diference
of strip 12 in BD and B30 horizons; PC 7 and the diferences
among strips in the 50 m distance; or the diferences among
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strips 8, 10 and 12 in BD and B30 horizons. ANOVA and
Post-hoc Tukey tests showed that only a part of these
visually found diferences (on interpolation maps) was also
statistically signifcant. The visualization of signifcantly-
diferent couples of sites by Post-hoc Tukey test can be
seen in Figures 9 and 10. This is a clear indication that the
general use of only maps or values (
e.g.
concentrations) is
insufcient; the visual observation of the data on its own
could provide false interpretation. In our case, ANOVA
showed that only part of the visually-observed diversity was
based on the data (not on map visualisation settings). It was
clear that the human activity tracers were more diversifed
with distance from the village than among the strips. PC 4
was more diversifed in both strips and distances than PC 7.
There were observed two basic patterns of diversity: 1)
diferences between mutually distant sites generally; 2) one
site being diferent from all other sites. The mutual distance
of two diferent sites infuenced the interpretation: the nearer
the sites, the more the diference could be interpreted as a
result of intentional management. The more distant, the more
it could be interpreted as a result of general management,
land use categories and so on. The frst pattern of distance
diferences was mainly observed along distances in the
strips (Figure 10 presents only sites of mutual distance under
400 m; for all distances, please see Figure 10.1 in SOM). We
could interpret this as a combination of land use categories
(arable felds, pastures, forests) and of the intensity of
management in these areas. It indicates that there were
few distinct changes or rapid gradients of management in
the strips. There was a threshold at the distance of 350 m,
recorded mainly by PC 4 in strip 4, 6 and 8. Both PC 4 and
PC 7 recorded that there was more diversity in the vicinity
of the village than in the distant parts of the feld system.
The second pattern was observed more among the strips
(Figure 9). This would indicate that for every distance there
was generally similar management intensity in all strips, but
in a few cases, management rapidly became diferent from
the one generally observed. We could probably see this as
a diference in management intensity. The diversity of both
patterns can be at least partially interpreted as the result
of a diversity of intentionally-placed management and its
intensity.
It should also be noted that there was no clear decreasing
pattern of the human-connected PCs along a distance
gradient. As can be seen in Figure 16.3 in SOM, PC 4
recorded roughly similar values in the village vicinity, which
then decreased in the distant parts of the feld system. PC 7
decreased in the village vicinity and then rose again in the
distant parts of the feld system. The smaller diversity among
strips has shown that there were diferences in management
among households, but the general pattern of feld system
structure was similarly followed by householders.
One could interpret the householders as utilizing the
possibilities of the independent management of their own
possessions, but generally they followed the usual pattern
of Waldhufendorf feld systems. The diversity based on
land-use categories still seems to be more profound than the
diversity based only on householder management strategies.
Furthermore, it should be stated that other processes could
also infuence the interpreted results. These are mainly:
1) diferent times for the performance of human activities;
2) diferent times for the abandonment of felds; 3) natural
processes such as leaching (although no clear and no positive
relation between human tracers and podzolization was
observed!); 4) other soil processes. Some of the above could
be clarifed by archaeological research of the households,
and some by more specialized pedochemical research.
4.5 Comparison with other studies
We have found that the decreasing manifestation of the
human-connected PCs with distance from the village cannot
be considered as correct. Such a general presumption of a
simple decreasing trend could not be accepted considering
the entire length of the parcel strips. Although we did not
sample the complete lengths (we do not know the actual
length, but it was probably longer than the sampled 1750 m),
the sampled parts showed non-linear trends in the human-
activity tracers. The general presumption of a decrease is
usually based on the research design: 1) sampling is not
continuous, but rather categorical as “infeld” and “outfeld”
(
e.g.
Davidson
et al.
2007, where the P values were higher
in the infeld than in the outfeld); 2) the sampling is linear,
but the felds are not sampled to a sufcient length (
e.g.
by
Součková
et al.
2013 who found a decreasing trend of δ
15
N
in the Spindelbach felds). The indications of a decreasing
trend were also based on historic evidence. Krenzlin (1952:
Figure 5) has shown that manured areas were spatially
adjacent to the built-up area of the village (with the note that
the village of that example was not Waldhufendorf). The
visualization of the manured area also showed that these
areas were not of the same extent among the parcel strips.
Unfortunately, we could not see the spatial distribution of the
manuring intensity. The diversifed intensity of manuring has
also been shown by Jones (2009). His study used a number of
shards as the bearer of information, and also showed that the
manuring not only had a connection to economic strategies
but also to purely cultural concepts.
Using the multi-element analyses, we found the following
elements somehow connected to the village: Zn, Sr and
possibly Mn (PC 2 and 4), and P standing alone in PC 7.
There are many studies focusing on multi-element analyses
bringing similar results (Bindler
et al.
2011; Bing
et al.
2011;
Costa 2011; Davidson
et al.
2007; Entwistle
et al.
1998,
2000; Facchinelli
et al.
2001; Horák, Hejcman 2016a; 2016b;
Sollito
et al.
2010; Walkington 2010; Wilson
et al.
2009). It
was also shown that it is highly suitable to work more with
the multivariate analyses results rather than with the original
concentrations, or the transformed concentrations,
i.e.
rather
than with generally only separate input variables, such as
elements. This was mainly shown, in the examples of PCs 1, 4
and 7, which separated the diferent inputs of phosphorus, the
main anthropogenic tracer above all (the diference between
the possibilities can be particularly seen in the comparison
of PC interpolations vs concentration interpolations – see
image/svg+xml
IANSA 2017 ● VIII/1 ● 43–57
Jan Horák, Tomáš Klír: Pedogenesis, Pedochemistry and the Functional Structure of the Waldhufendorf Field System of the Deserted Medieval Village Spindelbach,
the Czech Republic
55
Figures 26.1 to 26.4 in SOM). This approach is more used
in the geochemical literature (
e.g.
Facchinelli
et al.
2001)
than in the archaeological literature, where the analysis of
separate elements prevails (
e.g.
Bindler
et al.
2011; Wilson
et al.
2005), although in some cases multivariate analyses
are being used to fnd the connections (Entwistle
et al.
1998;
2000; Wilson
et al.
2008, 2009). There should also be more
research of soils in the areas of abandoned villages, not
only in general gradients or in regular grids, but also with
respect to diferent possessions. This has a potential not
only for human–soil relationships, but also to purely historic
questions.
There are also studies working with podzosols and
archaeological features (Kristiansen 2001). Our study has
shown that podzolization processes can be very rapid:
the macroscopically distinguishable E horizon was well
developed in the ploughed areas ca 600 years ago. Compared
to the study of Kristiansen (2001), we have found only one
indication of the possible relation between human activities
and podzol spatial distribution (PC 4, only the ratio of
horizons A to B30). PC 7 connected to phosphorus did not
reveal any relation to podzolization.
5. Conclusion
Our study has shown that multi-elemental analyses can
bring information not only about the identifcation of places
of historical human activities, but also information about
the internal structure of felds, which can be interpreted
in terms of management, its intensity, and the preferential
placing of felds. There was diversity between the parcel
strips and also, most importantly, diversity within the parcel
strips. Although some of this between- and within- strips
diversity could be explained by land-use type diversity,
some was explainable by household diferences and by the
preferences of peasants. The podzolization (or pedogenetic
processes generally) had covered any macroscopic traces
of ploughing. The spatial distribution of podzols revealed
it to be independent of the human activities or to have a
dependency only on particular activities – types of manuring
or soil improvement management. The research also revealed
that it is possible to obtain interpretable results by portable
XRF terrain measuring. Future research could focus on
using more methods (isotopic, general sedimentology – such
as grain sizes, organic content, pottery shard presence and
quantifcation,
etc.
) in interesting gradients, and also directly
on interesting places such as the glassworks or charcoal-
burning sites.
Acknowledgement
This research was supported by the Czech Science
Foundation, project No P405/12/P715 (T. Klír) and by
the Charles University Grant Agency, project No. 307415
(J. Horák). We also want to thank the Faculty of Arts of
Charles University, our students for their help with the
realization of this project, and Jiří Crkal for his useful help
and experience with Spindelbach. We also wish to thank the
reviewers for their helpful and inspiring comments.
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