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Pedogenesis, Pedochemistry and the Functional Structure of the Waldhufendorf Field System of the Deserted Medieval Village Spindelbach, the Czech Republic

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Spindelbach was a Waldhufendorf type of village, i.e. every household could manage its own fields 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 identified 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). Differences 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 differences were manifested by their intensity and by their spatial distribution.
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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 Horáka,b*, Tomáš Klíra
aInstitute of Archaeology, Faculty of Arts, Charles University, Celetná 20, 116 36 Prague 1, Czech Republic
bDepartment of Ecology, Faculty of Environmental Sciences, Czech University of Life Sciences, Kamýcká 129, 165 21 Prague 6 – Suchdol, Czech Republic
1. Introduction
Agricultural eld 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 identication
and mapping in their terrain and the classication of the
villages based on their eld 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 eld 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 (Homann 2014; Klír 2010a; 2010b;
Schreg 2013). That is to say, in European agrarian society,
eld systems have reected the socio-economic organisation
and every eld pattern has been intrinsically connected
with the specic 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 inuence 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: 15th December 2016
Accepted: 5th May 2017
DOI: http://dx.doi.org/ 10.24916/iansa.2017.1.4
Key words:
Medieval colonisation
Medieval-Modern Era transition
village economy
eld system ecology
podzol
multi-element analysis
phosphorus
ABSTRACT
Spindelbach was a Waldhufendorf type of village, i.e. every household could manage its own elds
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 identied 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).
Dierences 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 dierences were manifested by their intensity and by their spatial
distribution.
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
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 insucient 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 dierentiation among basic
archaeological features (houses, elds, hearths and so on), on
the verication 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 elds, 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 eld system
terraces, enabling the identication of elds belonging to
particular households; 3) it being a Waldhufendorf type of
village, i.e. an economic system where every household
could manage its elds completely independently of other
households; 4) the presence of other historical activities
unrelated to the village, but possibly inuencing 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
dierences among parcel strips (i.e. householder ownership)
and also within the parcel strips, and thus nd possible
management intensities and attitudes among householders;
and 5) to nd 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°2852.995N, 13°1142.143E) – 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 elds 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 eld system is based on the
system of parcel strips numbered upwards with altitude, and
distance, meaning the distance from households (since the
main eld 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 gures
and in tables. The terms used for spatial descriptions are
also related to distance from households: “village vicinity”
being the area of elds up to a distance of ca 350 m, and
the term “distant part” marks the area of elds 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 (13th)
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” eld system type in central Europe (by Schröder, Schwarz
1969: map “Die ländlichen Ortsformen in Mitteleuropa gegen Ende des
Mittelalters”).
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
45
strip no. 4, at the distance of 750 m). There were 13 parcel
strips identied, mainly on the basis of LIDAR data and
eldwork 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 at). 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 13th 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 elds (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 rst
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 shpond, 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, shponds, or meadows, were noted
in written sources from the 16th and 17th centuries; it can also
be found on the rst 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
“Gelängeur” 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
eld systems (e.g. Klír 2008; 2010a; 2010b; 2013; Klír,
Kenzler 2009). Waldhufendorf was a regular eld 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 11th to the 14th century
(Krüger 1967; see Figure 1 grey areas). This eld 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 eld pattern was
usually disrupted and the strips subdivided as a consequence
of socio-economic dierentiation (e.g. Born 1977, 167–170).
Figure 2. The examined part of the eld
system. The Prunéřovský stream is located
in the built-up area at the left edge of the
gure. Houses are located only along
this stream. The depicted altitude ranges
between ca 800 and 915 m above sea level.
The probes in elds 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 elds (strip 4, distance 750 m).
For a colour version, see Figure 2.1 in SOM.
0 2000 m
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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
46
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 uvial
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 at, 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 prole. 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 eld 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: elds 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 1st and 3rd
cm of that horizon, BD and B30 in every 2nd and 7th cm; also depths 30 and 40 cm were measured irrespectively of the horizon; † measured irregularly only
in few cases; See also gures 13.5.1 to 13.5.8. in SOM.
Cambisols* Podzols* Labels Used** cm Description
O O *** 0 Organic, not fully decomposed matter on the surface
A A A 1., 3. Dark, almost black organic-mineral horizon
no E E *** 1., 3. Eluvial, grey to white horizon, leaching zone
B B BD 2., 7. Darker facies of B horizon, accumulation zone
B B B30 2., 7., 30 B horizon, also accumulation zone, to 30 cm
B B B31–40 40 B horizon in depths 31 to 40 cm
B B *** B horizon deeper than 40 cm
C C *** C horizon – weathered bedrock, parent substrate
0 500 m
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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
47
proles, 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
rm 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 ocial 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 eld 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 elds 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 16th 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 SOx and NOx 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
proles. The areas managed in this way can be found in the
south-western parts of the village eld 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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Jan Horák, Tomáš Klír: Pedogenesis, Pedochemistry and the Functional Structure of the Waldhufendorf Field System of the Deserted Medieval Village Spindelbach,
the Czech Republic
48
The usual planting of young plants does not damage the soil
proles 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 elds: sampling for measuring δ15N 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 proles. 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 ve 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 identied 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 eld 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 proles 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 prole 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 nd any suitable place (the probe was
sampled, but the data was not processed in the analyses). We
made 120 probes in the elds and 5 probes for “background”
values. We included background probing and analyses to
reveal possible relationships of the elds’ geochemistry to
the presumably uninuenced environment. Since it was not
possible to nd an area comparable to the elds that was
denitely uninuenced 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 elds.
Indeed, the background probe sites were the only possible
places.
It should be noted that the elds-background relationship
was only secondary, as we primarily aimed at intra-eld
spatial diversity. We saw the amount from 120 eld probes
as sucient for obtaining the “intra-eld” 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
proles 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 dierent 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 eld-prole 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 prole 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, le
“Tables”, where the data is presented as a whole, and also
as data ltered 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
dierent 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 diusion
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 dierences between the strips (manifested
by dierence 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 dierences 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 rst gradient was along the distance,
the second gradient along the altitude. However, the part
of the elds 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 proles,
such as traces of ploughing and so on. The Figures 13.5.1 to
13.5.8 are good representatives of soil prole appearances in
the area of the elds. 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 simplied results; and SOM, le “Tables”,
for complete results). All analysed elements were strongly
connected to the rst two PCs. Although only the rst 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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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 1 PC 2 PC 3 PC 4 PC 5 PC 6 PC 7 PC 8 PC 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 % 46.70 68.74 76.98 83.73 88.44 91.82 94.48 96.22 97.86
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 dierence 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: dierences among strips. Segments indicate pairs of sites with statistically-signicant dierences.
Figure 10. Visualization of the Post-hoc Tukey test: dierences among distances. Segments indicate pairs of sites with statistically-signicant dierences.
Only pairs of sites of mutual distance under 400 m presented. For all dierences 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 dierences 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 dierent 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 rst
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 prole 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 dierent 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 sucient 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 eld 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 inuenced 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 ne 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 dierent: almost all elements recorded
dierences between “yes” and “no” podzols (Figure 15.1 in
SOM). However, the PCs recorded the dierences in only a
few cases: PC 4 recorded a dierence between A and B30
horizons; PC 7 recorded no dierence.
There were many places of charcoal burning. The spatial
distribution of the PCs mainly reected these sites in those cases
where the PC was related to Zn (PC 2 and 4). This was clearly
reected 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 inuenced 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)
reected 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 elds 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 elds
system, between distances of ca 550 to 950 m. It could be
seen on maps that this area had no substantial inuence 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 denitions 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 dicult 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 dierent P input into the soil
unrelated to human activity. A decision would require further
research. Generally, the diculty of nding an uninuenced
background is the norm in regions of dense settlement. The
Spindelbach example has clearly shown that it could also be a
problem to nd a background in extreme and marginal areas,
or, the design of “background” probes placement would have
to be based on dierent ideas to that of only “the background
can be found anywhere outside the human-inuenced 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 dierent 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 inuence
recorded in the elds, but would be combined with other
human activities not reected in the geochemistry of the
elds. The relation of the elds’ geochemistry to both the
background and to the built-up area should be analysed
in separate future research (not focused primarily on the
elds 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
dierent 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 proles.
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 nd 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 prole 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 elds) 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) eld
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 Dierences in land use and management
This was one of the main aims of this study: to nd out if
there were spatial dierences in human activity tracers.
Some dierences 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 dierence was observed between the village vicinity
and the distant parts of the eld 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 elds. 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 elds in the village vicinity; 2) arable elds
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 nding
of a whetstone (see Figure 12 in SOM) in strip 6, ca 1250 m
from the village. The management itself was diversied by
two tracers of dierent 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 elds. 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 dierences: PC 4 and the dierence
of strip 12 in BD and B30 horizons; PC 7 and the dierences
among strips in the 50 m distance; or the dierences 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 dierences (on interpolation maps) was also
statistically signicant. The visualization of signicantly-
dierent 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
insucient; 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 diversied
with distance from the village than among the strips. PC 4
was more diversied in both strips and distances than PC 7.
There were observed two basic patterns of diversity: 1)
dierences between mutually distant sites generally; 2) one
site being dierent from all other sites. The mutual distance
of two dierent sites inuenced the interpretation: the nearer
the sites, the more the dierence 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 rst pattern of distance
dierences 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 elds, 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 eld 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 dierent from
the one generally observed. We could probably see this as
a dierence 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 eld system. PC 7
decreased in the village vicinity and then rose again in the
distant parts of the eld system. The smaller diversity among
strips has shown that there were dierences in management
among households, but the general pattern of eld 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 eld 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 inuence the interpreted results. These are mainly:
1) dierent times for the performance of human activities;
2) dierent times for the abandonment of elds; 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 claried 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 “ineld” and “outeld”
(e.g. Davidson et al. 2007, where the P values were higher
in the ineld than in the outeld); 2) the sampling is linear,
but the elds are not sampled to a sucient length (e.g. by
Součková et al. 2013 who found a decreasing trend of δ15N
in the Spindelbach elds). 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 diversied 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 dierent inputs of phosphorus, the
main anthropogenic tracer above all (the dierence between
the possibilities can be particularly seen in the comparison
of PC interpolations vs concentration interpolations – see
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 nd 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 dierent 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 identication of places
of historical human activities, but also information about
the internal structure of elds, which can be interpreted
in terms of management, its intensity, and the preferential
placing of elds. 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 dierences 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
quantication, 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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... By the end of the 20th century, the number of geochemical analyses in archaeology had begun to increase and with it, also the spectrum of analysed elements broadened. In such studies, a multi-elemental approach was common, using mainly ICP-MS and ICP-AES or XRF techniques (e.g., Middleton and Price, 1996;Middleton, 2004;Entwistle et al., 1998;Wilson et al., 2005;2008;Hayes, 2013;Dirix et al., 2013;Hunt and Speakman, 2015;Salisbury, 2016;2020;Houfková et al., 2019;Š mejda et al., 2018;Horák and Klír, 2017;Horák et al., 2018;Simniškytė-Strimaitienė et al. 2017). Analysing a whole complex of elements also brought another possibility of data analysis: multivariate analyses in statistics (mainly principal component analysis -PCA). ...
... Such an approach enabled the interpretation not only of the elemental content, but also of the influence of different factors contributing to the input of the elements into the soil body (e.g., the geological background, modern pollution or past human impact). Multivariate analyses were used, e.g., by Salisbury (2013;2016), Horák and Klír (2017), Horák et al. (2018Horák et al. ( ), or Š mejda et al. (20172018). These approaches showed that there are many elements and their combinations recording a specific signal of human impact on the soil environment. ...
... Nevertheless, such elements are generally quite ambiguous in terms of interpretation and can be understood differently in different sites, contexts and regions. For instance, in some studies it was found out that Th reflected specific human activities , but in Bohemia Rb was usually found not to have been affected by any anthropogenic activity (Horák and Klír, 2017;Horák et al., 2018;Janovský and Horák, 2018). ...
Article
We present a geochemical analysis of a specific Iron Age type of site known as the Viereckschanze-a square enclosure located in Bělčice, southern Bohemia. We performed soil coring from the topsoil to ca 100 cm depth, with 200 cores (divided into 456 samples). The samples were measured using portable XRF and the final dataset comprised 16 elements (Al, Si, P, K, Ca, Ti, Mn, Fe, Cu, Zn, As, Rb, Sr, Zr, Pb, and LE-'light elements'). Because of the compositional character of data expressed in ppm, the data were transformed using isometric log-ratio transformation, which enabled them to carry out a multivariate analysis. This made it possible to determine the anthropogenic and natural content of elements. The site was specific when compared to usual archaeological sites for its 'unconventional' chemical signal: 1) the P signal typical for archaeological settlements was found mainly outside of the enclosure; 2) the conventional anthropogenic signal from the inside of the enclosure was only represented by Mn; 3) other elements related to possible anthropogenic activities were revealed only after applying statistical analysis (specifically As, Pb, Zn, Cu); 4) the unusual manifestation of Si and Ti (usually natural signals) strongly connected to anthropogenic contexts was observed. Increased contents of Cu, Zn and especially Pb were recorded in places indicated by previous magnetic measurements which were possibly related to an onsite metalworking activity. Such results could be characterised as a mixture of typical human-related signals (represented mainly by P and Mn) and typical natural signals (like Si, and Ti). These observations corroborate the hypothesis of a specificity of the Viereckschanzen. They did not have to be used exclusively for residential purposes and could have had a different, more complex socioeconomic role in the past. Last but not least, their occupation was probably also rather short-time.
... Elemental content in some cases reached presumed values and relations according to other studies focused on using PXRF in archaeological/paleo-landscape studies (Horák and Klír, 2017;Horák et al., 2018;Šmejda et al., 2017;. However, some of the results were in some aspects different from expectation based on those studies. ...
... Such methods usually work regardless of the measurement method or method of extraction. Previous studies have used, for example, the ICP method, but this generally works with other methods like PXRF (Horák and Klír, 2017;Horák et al., 2018;Janovský and Horák, 2018;Janovský et al., 2019;Šmejda et al., 2017;. Although PXRF gives the total content of the elements, studies using ICP usually work with just the fraction after digestion, which does not give total content. ...
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This paper focuses on the combination of geochemical methods and old map analysis to study landscape and settlement development. It is well known that historical land use of abandoned rural settlements affects soil chemistry and vegetation composition. We wanted to find out whether it is possible to distinguish various historical land uses when we know the current chemical composition of the soil; in particular, whether it is possible to recognize the presence of an abandoned village. Geochemical measurement was combined with old maps and grey literature analysis. The model area in the Romanian Banat Mountains is well documented by preserved old maps and is even documented by a land allocation plan from the beginning of the 19th century colonization. This unique document was compared with other old maps, and the spatial development of the rural settlement in the Romanian Banat was analysed. The geochemical methods revealed interpretable patterns, but in situations of little-known historical context (we do not know which households were really inhabited); the use of other supporting methods (archaeological topography, geophysics) is recommended. CITATION: ŠANTRŮČKOVÁ, Markéta, HORÁK, Jan and FANTA, Václav. Soil Chemistry to Support Old Map Analysis of the Built-up Area of an Abandoned Settlement. Case Study from the Romanian Banat. Interdisciplinaria Archaeologica, Natural Sciences in Archaeology [online]. 2020, XI(1), 103-115 [cit. 2020-08-18]. DOI: 10.24916/iansa.2020.1.8. ISSN 1804848X. Available from: http://www.iansa.eu/papers/IANSA-2020-01-santruckova.pdf
... In spite of these methodical obstacles, recent studies have highlighted the importance of peripheral areas, such as mountain ranges, mires, and sandy areas, either to supply medieval to pre-industrial centers with raw materials (ores, timber, tar) and energy (charcoal) (Knapp et al. 2013;Raab et al. 2015;Py-Saragaglia et al. 2017), or to produce energy-consuming goods like potash and glass (Cílová and Woitsch 2012;Östlund et al. 1998;Kirsche 2014). While previous studies have focused on the technology and composition of different Late Medieval glass types and their attribution to distinct regions in Germany (Wedepohl and Simon 2010) or Bohemia (Cílová and Woitsch 2012;Cílová et al. 2015), case studies on the spatial organization of the glass production sites and their environmental impact including geoarchaeological research and geophysical prospection are rather cursory in Bohemia (Křivánek 1995;Schmitt et al. 2006;Seidel et al. 2013;Horák and Klír 2017) but also beyond (Riols 1992). Although these activities must have triggered drastic changes in the local environment, historical sources often underestimate the development in these peripheral areas (Garnier 2000;Durand 2016) and archeological evidence is confined to structures like charcoal hearths or small activity areas, today mostly covered by dense forest (Schmidt et al. 2016). ...
... Apart from probably only seasonal mining activities (Tolksdorf et al. 2020), there are no indications for permanent prehistoric settlement of these upper reaches. Although historical records are scarce, the initial rural colonization in this region probably took place during the late 12th/thirteenth century and was followed by a phase of abandonment during the fourteenth century as indicated for the Hilmersbach site on the Saxonian side (Geupel 1994) and for the Spindelbach site on the Bohemian side (Horák and Klír 2017;Houfková et al. 2019), located north and south of the mountain crest. Fortifications at the Nonnenfelsen and at the Raubschloss Liebenstein sites (Geupel 1984a(Geupel , 1995 in the Schwarze Pockau river valley guard an important transition corridor towards Bohemia and infer that the economic development of this area during the late twelfth/thirteenth centuries may have been a purposefully conducted process fostered by local authorities (Fig. 1b). ...
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Since the twelfth century, forest areas in the upper reaches of the low mountain ranges of central Europe provided an important source of wood and charcoal especially for mining and smelting as well as glass production. In this case study from a site in the upper Erzgebirge region (Ore Mountains), results from archeological, geophysical, pedo-sedimentological, geochemical, anthracological, and palynological analyses have been closely linked to allow for a diachronic reconstruction of changing land use and varying intensities of human impact with a special focus on the fourteenth to the twentieth century. While human presence during the thirteenth century can only be assumed from archeological material, the establishment of glass kilns together with quartz mining shafts during the fourteenth century has left behind more prominent traces in the landscape. However, although glass production is generally assumed to have caused intensive deforestation, the impact on this site appears rather weak compared to the sixteenth century onwards, when charcoal production, probably associated with emerging mining activities in the region, became important. Local deforestation and soil erosion has been associated mainly with this later phase of charcoal production and may indicate that the human impact of glass production is sometimes overestimated.
... To refine our interpretation, we used PCA -as it could distinguish different inputs hidden within the total elements content in soil (e.g. Entwistle et al. 1998;Horák, Klír 2017;Horák et al. 2018). ...
... Areas which were not or only a little cultivated are now covered with podsols, but intensively-cultivated areas are covered with hyperdystric arenosols (by WRB, Entisols Psamments by USDA). However, the situation in the fields around the deserted village of Spindelbach in Krušné Hory (Ore Mountains, Erzgebirge) does not provide evidence of such a relationship (Horák, Klír 2017). ...
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Medieval settlement activities lead to the enrichment of nutrients in archaeological soils. The fundamental question we ask is whether large-scale mapping of soil horizons can be used to interpret former medieval activities. A portable X-ray fluorescence spectrometer (pXRF) was used to map the content of elements in soils over an area of 104.4 ha at the deserted medieval village of Hol, Czech Republic. Our methods were used to define differences in the geochemical composition of the soil in different parts of the village’s residential and field area (as a quantitative part of the research). Additionally we tried to interpret the results in terms of the variability of the natural environment and the medieval village (i.e. a more qualitative interpretational part of the research). Results of XRF spectrometry showed notable differences in element soil composition in different parts of the village. The presence of very low soil P content is probably caused by ineffective manuring practices in combination with the short duration of the agricultural cultivation. Nevertheless, soil P content helped us to interpret an area of gardens in homesteads IX, X and XI, where the presence of wooden constructions for agricultural purposes is presumed. Agricultural management at the deserted medieval village Hol was connected with organic waste and ash from homesteads (P, Sr, Zn, probably Mn). The spatial distribution of the soil content of elements and PCA allows us to claim that we can differentiate the functional parts of the village based on geochemical methods. At the site of the village we documented deteriorated natural conditions (pedological): for example, the underground water level and eluvial horizons. These conditions could have already been affecting the medieval village Hol. The deserted medieval village Hol does not differ from other deserted medieval villages, where a similar low agricultural fertility is assumed (for example, Kří).
... From an historicalgeographical point of view, Ervín Černý was the first to collect knowledge concerning abandoned villages and their agrarian hinterland and who divided it into several types and shapes (Černý, 1973; 1979). Historical field systems have also been the focus of natural science disciplines, such as pedology (Hejcman et al., 2013a), hydrology (Bayer, Beneš, 2004) and geochemistry Horák, Klír, 2017;. The first detailed multi-proxy analysis of abandoned terraced fields in the Czech Republic was undertaken in Malonín in South Bohemia. ...
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The historical field system of Valštejn represents one of the most extensive historical landscape complexes in the Czech Republic. Archaeological excavation of a former agricultural terrace (now a meadow) revealed the elaborate construction of a wall and stone foundation under the former arable field. This construction probably served for drainage and for soil protection. Archaeobotanical sampling facilitated the use of the charred plant material for radiocarbon dating of the soil profile, supported by the measurement of radionuclides 210Pb and 137Cs activity in order to estimate the age and stratigraphic integrity of the soil. An interesting record was obtained by archaeobotanical analyses of the lowermost layer, where wood charcoal and needles of fir (Abies alba) were identified and dated by AMS 14C. A discrepancy between the younger needle and much older charcoal could indicate an example of the old wood effect in archaeological chronology. The study has brought comprehensive results using environmental archaeology methods and sheds light on one of the stages of historical landscape transformation of the Early Modern Ages in central Europe.
... In addition to traditional indicators of settlement activities such as P, Ca, Zn, and Cu used in many previous studies, we identified other elements accumulated by settlement activities (Mg, K, V, Cr, Mn, Fe, Ni, Rb, Zr, and Sr). Based on our previous experience from the research of field systems in several deserted medieval villages in the Czech Republic (Horák and Klír, 2017;Horák et al., 2018), we can suppose that the accumulation of these elements can be the result of the ancient settlement activities. A similar conclusion, namely the accumulation of K and Rb because of fertilizer application on fields in Scotland in the 18th century, was recorded by Entwistle et al. (1998Entwistle et al. ( , 2000. ...
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Past human activities can be reflected in the elemental composition of contemporary soils. We asked how much historical land-use identified according to historical maps is reflected by the multi-elemental signatures of soils in an originally medieval village abandoned after WWII. Using X-ray fluorescence spectrometry, we determined the content of 24 elements in soil samples from former arable fields, field boundaries, forests, built-up area, and permanent grasslands. Previous human activities were connected with the accumulation of 13 elements such as the usually thus interpreted P, Ca, Zn, and Cu, but also with elements rarely used in archaeological studies such as Mg, K, V, Cr, Mn, Fe, Ni, Rb, Zr, and Sr. The content of P, Ca, Cu, Zn, Ni, Fe, V, Cr, and Zr decreased on former fields with the distance from the most enriched built-up area. This can be explained by the most intensive deposition of biomass ashes and manuring of gardens and fields close to the village. With the exception of Pb accumulated sub-recently because of aerial deposition, the lowest content of anthropogenic elements was recorded in continuous forest. The chemical signatures recorded were much stronger than those in previously studied medieval villages in the Czech Republic abandoned in the 15th or 16th centuries. This is because of the long period of the settlement’s existence since medieval times and in addition because of the short time since its abandonment. Although frequently neglected, the multi-elemental composition of soils in deserted settlements can be considered as cultural heritage similarly to the relicts of buildings or still visible field patterns.
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