Social spaces of daily life a reflexive approach to the analysis of chemical residues by multivariate spatial analysis
Social Spaces of Daily Life: A Reflexive Approach
to the Analysis of Chemical Residues by Multivariate
Sandra L. López Varela & Christopher D. Dore
Published online: 22 June 2010
# Springer Science+Business Media, LLC 2010
Abstract Studying human activities requires an examination of the inherent
epistemological problems in building arguments about the past based on chemical
residues and modern observations. A reflexive approach to the analysis of chemical
residues at the San Lucas archaeological site, a Classic Hohokam settlement located
in Marana, Arizona, represents a unique opportunity to evaluate current techniques
and paradigms for the interpretation of daily life activities. By incorporating an
innovative program rooted in satellite remote sensing image analysis and spatial
statistics, including new techniques, such as bulk density, loss on ignition, electrical
conductivity, and salinity, results suggest that soil chemical analysis will benefit
more from learning about structure and agency than from one single activity.
Keywords Chemical analysis of residues . Agency. Multivariate spatial analysis .
The number of publications discussing problems with the interpretation of chemical
signatures to define human activities has increased over the last decade (e.g.,
Hjulström and Isakssona 2009; King 2008; Wilson et al. 2008). This literature states
a certain degree of dissatisfaction related to the inability to link chemical elements to
human activities in archaeological and modern contexts. The difficulty in establish-
ing this one-to-one correlation, in some cases, is associated with the potential of
J Archaeol Method Theory (2010) 17:249–278
S. L. López Varela (*)
Departamento de Antropología, Universidad Autónoma del Estado de Morelos,
Av. Universidad 1001, Col. Chamilpa, Cuernavaca, Morelos 62209, México
C. D. Dore
School of Anthropology, The University of Arizona, Tucson, AZ, USA
instrumental techniques to document chemical residues recovered on human habita-
tion surfaces (Cook et al. 2006) to refine the relationship between past activities and
present soil chemical signatures (Terry et al. 2004). Other studies examine the effects
of site lithology on the geochemical signatures for human occupation (Oonka et al.
2009) or investigate the formation of anthropogenic chemical residues (Middleton
2004) to better define activities. Recently, Wilson et al. (2008) questioned the
rationale behind the interpretation of soil element signatures for identifying space
use and function, emphasizing that the problem originates in our uses of ethno-
graphic data to approach the past.
Essentially, the analysis of chemical residues to define human activities has never
been investigated as a philosophical problem. From an epistemological perspective,
how knowledge is created from geochemical data has never been examined in
terms of its foundations, pre-assumptions, and limits to validate the interpretation
of human activities. As already noted by Wilson et al. (2008), studying human
activities requires an examination of the inherent epistemological problems in
building arguments about the past based on chemical residues and modern
Here, we discuss the advantages of adopting an epistemological approach to the
analysis of chemical residues for the identification of human activities at the San
Lucas archaeological site, a Classic period (AD 1150–1350) Hohokam settlement,
located northwest of Tucson, Arizona. A reflexive approach to the analysis of
chemical residues represents a unique opportunity to evaluate what can and cannot
be achieved with our current uses of techniques and paradigms for the interpretation
of daily life activities in the past. In this study, we test the potential of soil
phosphorus, organic matter, carbonates, pH, and fatty acids in the identification of
human activities. Innovative in our analysis is our inclusion of bulk density (Db),
loss on ignition (LOI), electrical conductivity (EC), and salinity (TDS) tests to define
habitation surfaces. With such data, we explore the realms of interpretation by
incorporating a program rooted in satellite remote sensing image analysis and spatial
statistics to the study of human activity areas.
Equating Chemical Residues with Human Activities
Archaeologists began considering the potential of chemical residues to define human
activities after the influential investigations by Olaf Arrhenius (1929) on the soils of
Kagghamra in Sweden that demonstrated a correlation between high levels of
phosphate and fertile areas containing the remains of Viking farms and settlements.
Arrhenius’ rationale that high level of phosphorus are an indication of human
activities was applied in a later study in Norrland to identify a historic place where
three women accused of using witchcraft had been burnt. Concerned with the
ubiquitous presence of phosphorus in the soil, Arrhenius successfully correlated
phosphoric acid in the soil with bone fragments, identifying those locations. Later,
Arrhenius (1963) applied the same principle to define the distribution of
archaeological sites in the southwestern United States. Cross-cultural results
established phosphorus as indicative of human settlements, proving the value of
soil studies to archaeology.
250 López Varela and Dore
The potential of phosphorus as a significant indicator of human activity continues
under investigation by several scientists (see Holliday and Gartner 2007; Hutson et
al. 2009). In comparison to southwestern archaeologists, Mesoamerican scientists
enthusiastically adopted the use of phosphorus to define human activities (Barba and
Bello 1978). Specifically, Luis Barba incorporated semiquantitative tests, commonly
used in agronomy, to his field studies expanding the associations of a larger number
of chemical residues with human activity (Barba et al. 1991). The successful
application of his research program in the Maya region (Barba and Manzanilla 1987)
is the groundbreaking research supporting the current growth of chemical analysis to
determine human activities in Mesoamerica.
At a theoretical level, the definition of an activity area as one activity performed
in a specific area (Flannery 1976; Kent 1984, 1987) has structured the analysis of
geochemical data. The definition has encouraged scholars to correlate a specific
chemical element or compound to a particular activity. To illustrate the relationship,
results are represented as a composite map of anomalies by plotting the distribution
of each chemical residue under study as isopleths, becoming a standard
representation technique for most studies. To test the efficacy of chemical analysis,
Barba and his colleagues (Barba and Ortiz 1992; Manzanilla and Barba 1990)
considered ethnographic observations as a powerful tool for interpretation. Thus,
ethnoarchaeology became the specific field of study to test the significance of the
patterning observed in the archaeological record.
The reconstruction of human behavior in the past, based on modern observations,
is one tactic used by scholars to study the formation processes of the archaeological
record (Schiffer 1987). Several of these studies propounding the use of the present as
an effective strategy for the interpretation of soil chemical data from archaeological
sites are experiencing difficulties in defining the relationship between human
activities and chemical signatures (see Fernández et al. 2002). Ethnoarchaeological
investigations at Xaaga in Oaxaca, for example, isolated a low number (n=2) of
activities (Middleton and Price 1996, 680–681).
The use of ethnographic observations to support the interpretation of chemical
residues has certainly advanced our understanding of the past by developing new
methodologies and theoretical approaches. As discussed in the pages that follow,
there are boundaries to the construction of knowledge from the present and
limitations to the linking of a chemical element to a human activity.
Why the Failure for Interpretation?
The encountered limitations have different theoretical sources. Mostly, these were
derived from a generalized static view of the past, embedded in an early
understanding of the archaeological record as containing rich assemblages of in
situ objects in their loci of use. Although many behavioral archaeologists have
already abandoned the in situ idealistic view of the past (see, for example, arguments
presented by Binford 1981), this theoretical orientation has been of great influence to
the study of chemical residues to interpret human activities.
Linked to this early approach to the study of human activities, we argue, too, that
the definition of an activity area is also part of the problem. Mainly, archaeologists
Multivariate Spatial Analysis of Chemical Residues at a Hohokam Site 251
assume that only one activity takes place at a specific location (Flannery 1976, 5–6;
Kent 1984, 1; Manzanilla 1986, 11). This definition introduces a static conceptu-
alization of the use of space. This correlation tends to oversimplify human space use,
disregarding that humans move in space and time to accommodate the needs of
everyday life. The use of space is dynamic.
Human activities are the result of conscious learned decisions concerning the
locations at which a diverse range of activities will be performed (Hodder and
Cessford 2004; Kent 1984). Every time an activity takes place, individuals reproduce
their social world. If we would consider that these daily activities do not always take
place at the same exact location, rather within a certain range in space, we would
confront that different multiple activities overlap at a particular location (Dore and
López Varela 2004; López Varela 2005). This realization compels a different
rationale to analyze and interpret a collected sample in the field, as it is carrying the
chemical residues of many activities differentially taking place in time.
Also, advances in the application of soil chemical analysis to define human
activities are increasingly demonstrating that chemical residues found in an
excavated area are not always the result of human activity and not all human
activities affect or deplete, for example, soil phosphorus levels (Holliday and Gartner
2007; Sánchez and Cañabate 1998). By inquiring about how chemical residues are
deposited on surfaces, it becomes clear that natural processes are involved in adding,
subtracting, and altering chemical concentrations on surfaces (Middleton 2004). Fur-
thermore, the atmospheric particulate matter could play an important role in the chemi-
cal enrichment of heavy metals. For example, pollutants are rich in heavy metals, and
these might be influencing the chemical characteristics of modern surfaces.
Even if we consider that chemical residues are deposited by natural conditions,
their absorption and concentration might be subjected to human-induced activities
such as sweeping. If sweeping takes place on a daily basis, the probability that a
chemical element originating from a natural process or a human activity accumulates
or decomposes in the surface may be raised or diminished. If sweeping is a more
sporadic activity, chemical residues might tend to concentrate in certain areas and
later further removed or dispersed by further sweeping. If the episode of cleaning
involves water or soap, these may induce a reaction, giving place to new chemical
compounds. If accumulation of waste, objects, or dust is taking place in a surface
that requires cleaning, it means that many other activities are shedding residues.
Chemical residues trapped in this surface represent palimpsests—traces originat-
ing from the human body, the materials involved in different type of activities, and/
or natural processes. It is only logical to ask how we can correlate a chemical
element to an activity (see Wilson et al. 2008), if the chemical element in a sample
might be the result of many activities or natural processes. To answer this question,
archaeologists have either worked under the premises of middle-range theory or
introduced instrumental techniques to differentiate between the human and non-
human factors as agents for chemical enrichment of surfaces.
The Ethnoarchaeological Approach
Ethnoarchaeology works under the premises of middle-range theory, suggesting that
some processes at work in the ethnographic present are identical to the processes that
252 López Varela and Dore
took place in the past. Chemical signatures in the present establish the connection to
the dynamic processes in the past. However, chemical signatures need to be placed
in a social context to acquire meaning. Chemical signatures cannot be turned into
concepts until they are given meaning (Binford 1983, 413) through middle-range
For archaeological interpretation, middle-range theory as an intermediary
analytical process to general theory building is unsuccessful because it acknowl-
edges that the activities taking place in the present equate to those taking place in the
past (Johnsen and Bjornar 2000). The selective transfer of information from one
context to another, contemporary to past communities, falsely assumes that the lives
of those that are studied in the ethnographic context have remained unaffected for
centuries (Thomas 2004). Thus, the meaning for the targeted activity in the past has
changed through time.
When middle-range theory is used to give meaning to a chemical signature, we
introduced an error in the interpretation of the past. The paradox here is that middle-
range theory promised to be a procedure entirely separate from our ideas concerning
what happened in the past (Thomas 2004, 72). However, this is hard to claim as we
are providing meaning from the present to a chemical signature of the past (Thomas
2004, 75). The ethnographic context is already preconceived, as it is understood
under the analogy that past and present are the same (Thomas 2004, 240).
A linear and uniform approach to the ethnographic context introduces a bias to
the interpretation of chemical signatures in an archaeological context. According to
Thomas (2004, 241) “...the most important role of ethnographic analogy lies not in
filling in the gaps in our knowledge of prehistoric societies but in troubling and
disrupting what we think we already know”. Analogies withdrawn from the
ethnographic record aim at establishing a testable hypothesis about what the past
was like, instead of taking them as measurements of presumed similarity. Looking
for answers to, what if the past was like this (Thomas 2004, 241), sets up a kind of
analysis aiming to understand how the similarity has been modified and recon-
textualized by human agency. In other words, the approach reconsiders humans as
active individuals influencing the deposition of chemical residues while reproducing
their daily life activities (see Dore and López Varela, in this volume).
The Instrumental Approach
To correlate a chemical element to an activity, archaeologists have introduced
semiquantitative and instrumental techniques to differentiate between the human and
non-human factors as agents for chemical enrichment of surfaces. These techniques
have provided invaluable data for the interpretation of space use in and around
archaeological remains, to define the extent of human activity beyond the structural
remains, and to locate archaeological sites (Wilson et al. 2008). The challenge to
determine the correlation between the chemical elements left by human activities has
introduced the need to cope with multi-element data through a complete statistical
approach (Middleton 2004; Wells et al. 2004) and to distinguish them from the
fraction that is available in the soil solution, the nutrient-laden free water in the soil.
In fact, the challenges faced by these investigations have refined uses of instrumental
techniques. The use of inductively coupled plasma-mass spectrometry (ICP-MS) has
Multivariate Spatial Analysis of Chemical Residues at a Hohokam Site 253
raised questions about the chemical interference of aggressive acids for soil extrac-
tion (Cook et al. 2006). This method uses nitric acid for soil extraction instead of
dilute hydrochloric acid (HCL) that generates silver chloride (AgCl), interfering
strongly with the technique (Cook et al. 2006). Mild acid-extraction agents used
with inductively coupled plasma-atomic emission spectrometry (ICP-AES), such as
HCL, are suggested as effective means of extracting chemical residues from a
sediment modified by human activity and powerful enough to extract complexed and
adsorbed ions (Middleton 2004; Wells 2004) and neutralize high concentrations of
calcium carbonate. Alternatively, diethylenetriaminepentaacetic acid chelate has
been introduced as an alternative method to extract trace metals in combination with
ICP-AES (Fernández et al. 2002).
The increased application of these techniques is demonstrating both their potential
and their limits in distinguishing separate activity areas (Cook et al. 2006; Hjulström
and Isakssona 2009). Knowledge created from the application of these techniques is
limited because it is also important to consider that individuals influence the
deposition of chemical residues while reproducing their daily life activities. Chemi-
cal enrichment of surfaces occurs, to a certain extent, because human activities are
The research in the application of instrumental techniques, in most cases, is con-
cerned about finding the right number of chemical elements to be optimal in defining
human activities. The Laboratory for Archaeological Chemistry at the University of
Wisconsin—Madison, for example, defines with ICP-AES twelve chemical elements
considered to be representative of human activities such as food preparation,
cooking, consumption, disposal, ritual, and transit areas (Middleton 2004; Middleton
and Price 1996; Terry et al. 2004; Wells et al. 2004). The selected set includes
aluminum (Al), iron (Fe), calcium (Ca), sodium (Na), potassium (K), magnesium
(Mg), titanium (Ti), and phosphorus (P). These studies, by considering this set of
elements, have certainly contributed to the definition of these activities in the past.
In a recent study at Cancuen, Cook et al. (2006, 636) encountered additional
activities by considering a larger number of chemical elements with ICP-MS. The
consideration of a total of 60 chemical elements detected elevated concentrations of
gold in floor surfaces up to seven times that which exists naturally in calcareous
soils, but this signature could not be securely attributed to a particular activity (Cook
et al. 2006). Since the manufacture of gold for this area and time is not plausible, it
was suggested that this metal could be related to “Galactic Gold”, a particular kind
of black jade still not found at Cancuen (Cook et al. 2006, 638) that is characterized
by inclusions of precious metals including gold. Incorporating a larger number of
elements established the possibility of detecting activities related to the working of
jade. From the Cancuen study, archaeologists learned that there is a large number
of activities that remain undetected if only a set of twelve chemical elements is
considered. Clearly, the set of twelve chemical elements will provide a standardized
view of the activities that humans performed in the past. On the other hand, eight
chemical elements in this given set are regarded as the most abundant chemical
elements on earth. In fact, Cook et al. (2006, 632) disregarded five of these chemical
elements in their study to better distinguish the activities occurring in space.
Considering a set of 60 chemical elements is not the answer to identifying a larger
number of activities, but in considering that humans are social individuals using
254 López Varela and Dore
space according to the world they are embedded in. This world is experienced
individually, as each person negotiates uniquely with the social environment,
structuring the whole complex of habituated activities of ordinary living (Farnell
2000) in an individualistic way. If we consider that humans have individual
motivations and desires, every time we approach the archaeological and ethno-
archaeological record, we will be confronted with unique activities that might need
fewer or a larger number of chemical elements to be detected. This realization
compels the analyst to adjust instrumental techniques to this new challenge in order
to investigate the social meaning of chemical residues.
In deconstructing the rationale of our current uses of instrumental techniques, it is
important to notice that archaeologists are projecting their social world views, their
Weltanschaung, to interpret the past. Chemical analysis of floors has created a
scientific discourse that, even in the presence of archaeological materials, the
interpretation of human activities by the archaeologists is guided by the authority of
instrumental techniques. In those ethnoarchaeolocgical cases that ICP-AES takes
into account additional trace metals such as copper (Cu), mercury (Hg), or lead (Pb),
their presence is associated with modern industrial objects (see Fernández et al.
2002). For example, when zinc (Zn) was identified at Las Pozas, Guatemala, its
origin was attributed to metal coating on cans, rubber tires, or batteries (Fernández et
al. 2002). If we were going to find elevated concentrations of metals in an
archaeological context, most likely, we would interpret their presence as the result of
production activities (see Terry et al. 2004).
A metal like Zn is not only present in “inorganic” objects. Zinc is present in
organic products, such as, pork, sardines, pumpkin seeds, or shellfish. What if the
presence of Zn is the result of an organic product? Again, the invaluable con-
tributions of Barba to the study of human activities already have attempted to define
fatty acids, carbohydrates, and proteins with semiquantitative techniques. However,
there are useful methods to identify organic residues such as high performance liquid
chromatography (HPLC) used extensively in biochemistry. HPLC is not foreign to
archaeology, as this method has been used to identify lipids (Passi et al. 1981) or
organic coloring of textiles (Karapanagiotis et al. 2007). HPLC is a powerful method
to identify and separate a target chemical compound, by purifying it from a mixture
of chemical compounds and at the same time quantifying its unknown concentration
in a known solution. In soil science, HPLC is combined with inductively coupled
plasma time-of-flight mass spectrometry or with X-ray fluorescence spectrometry
(van Campenhout et al. 2008). With great certainty, quantitative organic chemical
analysis to the study of human activities will very soon be part of the archaeological
literature as more scholars are beginning to notice the importance of considering
organic residues to define human activities (e.g., King 2008; Hjulström and
Adopting a Social Paradigm
The influence of epistemology on archaeology has prompted an explicit consider-
ation of the role of field and laboratory methodologies for data collection, analysis,
and interpretation (e.g., Lucas 2001; Shanks and Hodder 1995), as the way in which
Multivariate Spatial Analysis of Chemical Residues at a Hohokam Site 255
archaeologists engage with archaeological data has direct consequences for our
interpretation of the past. As we have already discussed, the methodological
approach to the study of human activities has been supported by both instrumental
and semiquantitative techniques (see Middleton et al., in this volume). Research
history confirms that human activities leave residues on the surfaces of habitation
and that chemical analysis is a viable method to study them. However, efforts to
enhance the act of archaeological interpretation have been limited. Despite the
recognition that many different activities take place in a single space, when it comes
to the interpretation of residues left by activity, results are expressed as a one-to-one
correlation. Some of our colleagues do not agree with us (see Middleton et al., in
this volume) that the interpretation of data is presented and visually reconstructed as
a one-to-one association, for example, carbonates to food preparation. In this
volume, Dore and López Varela discuss how this approach was unable to represent
the dynamics of space use in an ethnoarchaeological case (see Pecci et al. 2010).
Relying on other pieces of information such as artifacts is a plausible solution.
However, this solution only transfers to other realms the inability of our current
methodologies to account for the other activities taking place in a single space. We
raise this concern because we have powerful tools to address these issues. We
believe that if we aim our uses of technology not only to determine the chemical
composition of the activity but also to address its social components, we will extend
the potential of our methodologies.
The identification of human activities through chemical analysis requires an
understanding of the social and spatial settings in which the practice of everyday life
takes place. It is important to recognize that the use of space is dynamic and
organized by social practice (Dore 1996; López Varela 2005; Dore and López
Varela, this volume). These characteristics will influence chemical enrichment and
interpretation. Every activity has a beginning and an end, and time is a condition for
actions to emerge and to transition from one action to the next (de Certeau 1988).
Despite suggestions that the diachronic variation in the use of space is not
problematic (Middleton 2004), time poses a real challenge for the interpretation of
human activities and for understanding the chemical enrichment of surfaces. Over a
long period of deposition, the original chemical signature of the activity will start a
process of “decomposition”. In the archaeological record, we will recover a chemical
fraction of the activity.
The passage of time is what makes an activity a daily or a seasonal event, giving
meaning to space. In a modern context, for example, we were able to observe the
differential uses of space by a woman potter. In the morning, a specific area could be
used to prepare food. Later in the day, this same area might be used for making
pottery and even later, it could be used to place a mat to sleep upon (López Varela
2005). Movement and time are conditions for activities to take place and to be
repeated in space, both influencing how residues will be deposited on the surfaces.
When humans perform an activity in space, they move within variables of direction,
velocity, and time. In between what we call activities, many other types of actions
are taking place as well, such as walking or resting.
At the end of the day, a particular space has received successive depositions of
many chemical residues, originating from diverse activities. Every year in
November, the same space in which the potter sleeps and makes griddles is
256 López Varela and Dore
transformed into a ritual space. The repetition of activities in a given time will
influence how chemical residues are absorbed, decomposed, preserved, or dispersed
on a surface. For the interpretation of the activity, it is necessary to recognize that the
repetition of activities is the materialization of people’s actions.
There are other variables influencing the chemical enrichment of surfaces,
developing within the realm of the social, that are important to consider if the goal is
to assign space functionality or to determine human activities with chemical
elements, such as space.
Space itself imposes boundaries to the human body, allowing or restricting the
performance of activities. For an activity to take place, humans need to remember
the locations at which a diverse range of activities will be performed (Hodder and
Cessford 2004). The repetition of activities takes place because humans are guided
by the knowledge of how to do things. The ways individuals do things are
determined by rules provided by the world they live (Giddens 1981, pp. 54). The
process of learning and memorizing these rules is individually experienced. It is
expected then that the repetition of activities might be similar, but not identical, each
time they are performed. Apparently, these activities do not leave residues but they
materialize with the repetition of activities.
All of these social variables are important to consider for the interpretation of
space use, as the variability expressed by the chemical data could be the result of an
individualized expression of a particular activity. Humans perform activities because
these are socially embedded and individually experienced. These social character-
istics of activities are important to consider, particularly, when the analyst will
extrapolate the result to another site or feature.
The spatiality of daily life gives meaning to space, creating a practiced place (de
Certeau 1988). The intensity and diversity of human activities are measures of
importance in understanding the structuring of agency. These measurements suggest
the dynamism of everyday life. In this regard, chemical residues are telling us about
the structuring and organization of socialized actions, not only about a specific
Here, we would like to suggest that soil chemical analysis would benefit more on
learning about structure and agency. If we were to understand the structuring of
social practices, then, we will be in a position to direct technology to address the
practice of everyday life.
A Heuristic Approach to Soil Chemistry Analysis at the San Lucas
Archaeological Site in Marana, AZ
In the Hohokam region, archaeologists support their interpretation of human
activities and space use based on historic documents and ethnographic observations
of the Pima, Papago, and Maricopa populations (Seymour and Schiffer 1987,
pp. 588). This is related to the scarcity of artifacts on archaeological floors and to
the burning of structures during site abandonment (Eric Klucas, personal com-
munication 2004). Hohokam archaeology has focused on the house as an analytical
unit to understand social organization. As in many other archaeological cases, the
characteristics and the location of architectural features and objects are studied as
Multivariate Spatial Analysis of Chemical Residues at a Hohokam Site 257
evidence of social complexity (Crown and Fish 1996). Based on investigations at
Snaketown, several activities have already been recognized from features and
artifact distribution in these structures (Seymour and Schiffer 1987). Variability in
size, form, and distribution of pits suggests that some of these features were
suitable for cooking and others were used at night for heating (Seymour and
Schiffer 1987, pp. 588). Based on ethnographic observations, posthole alignments
in association with large pits are similar to those used as outdoor kitchen areas by
the Pima, Papago, and Maricopa (Seymour and Schiffer 1987, pp. 588). Some
houses appear to have served a wide range of functions in that they contain
evidence not only of domestic and craft-related activities, but also, of storage
(Seymour and Schiffer 1987, pp. 586). In the case of production activities, such as
pottery making, these areas are assumed to have been located in the middle of a
cluster of houses (Seymour and Schiffer 1987, pp. 589–590). Ethnohistoric sources
refer to the Pima and Maricopa sleeping on mats of woven reeds or plant fiber
(petates) on each side of the hearth (Seymour and Schiffer 1987, pp. 585).
Similar spatial arrangement of structures, open spaces, and pits are normally
interpreted as a household courtyard group, sharing a diverse set of activities, not all
of them domestic in nature (Abbot 2000; Seymour and Schiffer 1987; Wells et al.
2004; Wilcox and Sternberg 1983). In general, these Classic Hohokam settlements
are characterized by wattle and daub structures built around shallow pits, with sets of
2–4 dwellings clustered around a main plaza (Plog 2003, pp. 73). The Classic dietary
system of the Hohokam included meat that was acquired by hunting of rabbit, deer,
bighorn sheep, fox, or raccoon (Bayman 2001). Agave cultivation was one of the
main economic characteristics of the northern Tucson Basin (Fish et al. 1992).
Archaeologists suggest that craft production of pottery and marine shell objects were
undertaken by non-elite household dwellers and that these were traded for other kind
of resources (Bayman 1999). These developments may be evidence of social
differentiation and the existence of elite groups.
The San Lucas Project
In 2004, Statistical Research, Inc. (SRI) initiated excavations at the San Lucas
archaeological site, in Marana, Arizona. The San Lucas village was probably
integrated to the nearby Marana Mound community (Fish et al. 1992). Excavations
at the San Lucas site are part of an applied archaeological project. While not
typically undertaken at Hohokam sites, chemical analysis as a method for defining
activity areas at the site was implemented as an innovative idea with research merit.
The application of chemical analysis to the study of human activities lost its impetus
in southwestern archaeology around 1965 (see as an exception Whittlesey et al.
1982). The analysis designed for the San Lucas project is unique in the region, in
that (1) it is a comprehensive study that expands techniques previously used to
determine human activities; (2) it incorporates a program of statistics and spatial
analyses for the study of human activity areas; and (3) it critically evaluates field
Given the constraints on this project, work required the use of methods that could
rapidly assess and define activity areas within a budget that prohibited the
incorporation of instrumental techniques. The use of quantitative tests commonly
258 López Varela and Dore
used in agronomy to determine soil properties and their suitability for agricultural
purposes were proposed. These tests are inexpensive and easy to perform in the
laboratory, yet robust enough to identify potential markers of human activities, such
as soil phosphorus, organic matter, and carbonates (see Middleton et al., in this
volume). To measure fatty acids, a semiquantitative technique was used.
For the San Lucas site, distinguishing archaeological floors from the natural soil
is not clear in certain areas, mostly due to erosional–depositional processes, but also
due to the burning of structures, making it necessary to investigate the properties of
the surfaces and to determine if human activities took place on archaeological floors
or on a modified soil terrain. To answer this question, we incorporated bulk density
(Db), loss on ignition (LOI), electrical conductivity (EC), and salinity (TDS) tests to
distinguish between these two types of surfaces.
Given the complexities in the identification of specific activities in the archae-
ological record, instead of identifying a precise activity, it was decided to learn from
the structuration of these chemical residues and to recognize the dynamic uses of
space. Structuration is visible to archaeologists because of our capability of
examining temporal spans (Joyce and Lopiparo 2005). To investigate the basic
assumption that empirically recoverable chemical data may provide evidence of the
practice of everyday life, we have developed a suite of premises that are tested by
means of rule-based approaches combined with map algebra. For Mesoamerican
studies, the identification of floors is not a major issue. If a simple decision rule is
used, such as the research questions we are addressing in this analysis, then the
outcome of each implementation of the rule will produce a yes or no answer
(Wheatley and Gillings 2002). To reconstruct the dynamic uses of space, we use
remote sensing image analysis techniques to identify structure in the data, departing
from plotting single chemical residues in space as isopleths promoting that only one
activity took place in space.
The Chemical Survey of the San Lucas Archaeological Site
Archaeological investigations at the San Lucas site defined five adobe structures,
open spaces, and a variety of pits (Fig. 1), covering 650 m2
. In this area, considering
our sample (n), we initiated a systematic chemical survey of a 650-m2
using a 1-m grid to learn about the social uses of space. To obtain the samples, an
electric drill was used to perforate the surface up to 5–8 cm in depth. In surfaces
made hard from burning (including interior floors and walls), a 2.5-cm diameter bit
in an electric drill was used to perforate the surface up to 5–8 cm in depth. A trowel
was used to penetrate the surface instead of the drill when softer sediments permitted.
To avoid introducing our predetermined conceptions of the uses of space,
sampling was not guided by the presence of architectural features, since we also
consider these elements as a palimpsest of discrete events. The chemical survey
yielded a total of 650 samples. However, to save time and to reduce laboratory
expenses, we selected a subset of 172 samples, obtaining an off-set systematic
spatial sample with point spacing approximately every 2 m (1 point per 3.33 m). The
chemical analysis of 172 samples provided us with a representative approximation of
the uses of space, allowing us the flexibility to process additional samples for more
intensive research at a later stage.
Multivariate Spatial Analysis of Chemical Residues at a Hohokam Site 259
Rapid Assessment Techniques for Chemical Residues
Characterizing the type of surface where human habitation developed is of relevance
to the chemical enrichment of surfaces, as it may influence preservation, absorption,
and decomposition. We decided to test several premises to determine (a) if the
sampled surfaces were natural soils compacted by human activity, (b) if these
surfaces were artificially created, and (c) if chemical residues remained despite
abandonment practices and excavation procedures that tend to remove thick layers of
To achieve these goals, López Varela and Palacios-Fest determined the water
contents, the presence of organic matter, and the identification of calcium carbonate
for all samples with a loss-on-ignition (LOI) test. Additionally, the 172 samples were
tested for pH levels, electrical conductivity, and salinity contents, as well as for
contents of phosphates. For every sample, we measured the physical characteristics
of the soil, such as color and weight, with and without gravel.
Fig. 1 The excavated area with the location of structures and features that were sampled for chemical
analyses (Illustration by Christopher D. Dore)
260 López Varela and Dore
Phosphates To measure phosphate contents for each sample, we used a Mehlich-II
dilute acid extraction. Concentrations were measured with a spectrophotomer. So,
2 g of sample were placed in a 60-ml plastic bottle and were mixed with 25 ml of 1:6
dilute Mehlich-II solution. The plastic bottles were mounted in a hollowed tray that
was later placed in a shaker for 10 min. Sets of containers were prepared with funnel
and filter paper to filter the solution and to recover liquid. Standards at 0.1, 0.5, and
1.0 mg/L of PO4 and blank (distilled water) were prepared. The colorimeter was set
up for Program 79 and calibrated to read PO4. Colorimeter vials were labelled with
appropriate sample number. Then, 1 ml of filtered solution was placed in vial and
filled with 10 ml of distilled water. One pillow of PhosVer3 reagent was added and
shaken vigorously. The vial was placed in the colorimeter chamber and the value
was read. The reading was repeated after running the first batch.
Bulk Density (Db) Bulk density is defined as the mass of soil per unit volume in its
natural field state, including air space and mineral plus organic materials. It is a test
commonly used to learn about the potential of a soil for crop productivity, erosion,
and leaching of nutrients. The purpose of this test, namely, the clod method, is to
distinguish natural soils from archaeological surfaces based on density and porosity.
Bulk density can only be measured in a soil with well-developed structure, for
example, in a soil that is cemented. Soils with high Db values impede root
penetration and adequate aeration so potential for agricultural purposes is
diminished. The “clod method” that estimates total water storage capacity when
the soil moisture content is known (Evanylo and McGuinn 2000). For each sample,
the volume was determined by weighing 1–3 clods in air and by coating the clod
with wax for its immersion in water, making use of Archimedes’ principle. However,
López Varela, Palacios-Fest decided not to follow the customary procedure of
repeating the sample until an ideal number is found below 5% in density. Here, we
depart from this procedure to understand higher density values, as there are rocks
that exhibit much higher values in density such as feldspars, dolomite, sandstone,
quartz, or limestone.
Loss-On-Ignition Test This is a fast and inexpensive means of determining not only
organic matter, but also water and carbonates with precision and accuracy
comparable to other sophisticated analysis. The procedure involves weighing the
sample in a crucible that was exposed to three different temperatures in a Paragon
Touch and Fire DTC 800 furnace. The samples were processed to estimate water
contents, the presence of organic matter, and calcium carbonate in the samples. The
procedure includes weighing of the crucible before it is exposed to heat.
Approximately, 1 g of the sample is added to the crucible. The exact weight of
added sample is calculated by determining the mass of air-dry soil. Then, each
crucible with 1 g of sample is heated to 105°C in the furnace for 12 h to eliminate
the water in the sample. Then, each crucible with the reheated sample is weighed to
determine the loss of water. The percentage of water is then calculated.
The second step includes reheating the sample to 550°C for 4 h to determine the
loss of organic matter that is oxidized and leaving possible ash residues. After the
sample cooled down for 15 h, the crucible is removed from the furnace and placed in
the desiccator for 20/30 min. Then, the sample is weighed once more to calculate the
Multivariate Spatial Analysis of Chemical Residues at a Hohokam Site 261
new mass. The difference between the mass of the crucible and the new mass is
equivalent to the amount of organic matter in the sample.
The third step includes reheating the remaining sample to 900°C for 2 h and a
cooling period of 20 h at 105°C. The reaction releases carbon dioxide (TIC) in the
presence of calcium carbonate (CaCO3) at 950°C, leaving oxide residues. The sam-
ple is weighed again. The difference between the mass of the crucible and the new
mass is equivalent to the amount of carbonates in the sample.
pH, EC, and TDS Tests The alkalinity and acidity of the soil were measured with a
pH meter, as were electric conductivity (EC) and salinity (TDS). EC is the ability of
the soil to conduct an electrical current and is measured by introducing an electrical
current through a soil sample solution. Salinity represents the total dissolved solids
(TDS in milligrams per liter). It is a soil property referring to the amount of soluble
salt in the soil. Plants are severely affected, both physically and chemically, by
excess salts. Excess salinity is generally a problem in arid and semiarid regions
because a large number of soluble salts can be found in these soils, along with calcite
and carbonates that can buffer soil pH. To measure pH, 10 g of every sample were
weighed, placed in a container, and diluted in 10 ml distilled water. The sample was
vigorously mixed and allowed to rest for 15 min. A pH meter electrode was
introduced to read the value in the meter and the measurement was taken again after
a couple of minutes. The meter was then changed to measure EC and TDS modes to
read electrical conductivity and salinity, respectively. Measurement was repeated
after a couple of minutes.
To explore the potential of finding fatty acids, we measured their presence in the
samples following a simple technique developed by Barba et al. (1991). The
technique assesses the presence or absence of fatty acids by weighing 0.05 g of
sample and making it react with chloroform, ammonium hydroxide, and hydrogen
peroxide. This test quantifies the presence of fatty acids on a qualitative scale,
ranging from absent to very abundant.
A detailed description of test procedures for these techniques are included as part
of an appendix.
Defining the Surfaces of Chemical Enrichment
A soil is understood here as a complex natural body formed through time in
previously unweathered sediment under the influence of plants, microorganisms, and
soil sediments (van Breemen and Buurman 2002).
Premise 1. If the surfaces associated with human habitation at the San Lucas sites
exhibit the chemical, physical, and biological characteristics that
enable soils to perform a wide range of functions, then these surfaces
are natural soils that were compacted by human activity.
Following soil science conventions, we differentiate between anthrosols and
archaeological floors. According to the European Soil Bureau Network, anthrosols
are characterized by at least one or more of the following diagnostic horizons: hortic,
irragric, plaggic, terric, or ananthraquic with underlying hydragric horizon, resulting
from deep or wet cultivation, long-term irrigation, or the addition of compost or
262 López Varela and Dore
sods. None of these horizons typify the habitation surfaces analyzed. When soils are
comprised of anthropogenic material such as urban waste or mine spoil, these are
considered by soil science as technosols—soils whose properties and pedogenesis
are dominated by their material origin, measuring between 50–100 cm in depth.
Archaeological floors are closer to technosols in their definition. These are formed
by the layering of lime or mortar, covered by plaster and then coated with a wash
(Littman 1962, pp. 100). The top layer seals the influence of natural soils under
normal conditions making them suitable to preserve chemical residues left by human
activity or natural process.
In contrast, soils play a dominant role in the biogeochemical cycling of water,
carbon, nitrogen, and other elements, influencing the chemical composition and rates
of substances in the atmosphere and the hydrosphere. The main physical processes
influencing soil formation are movement of water, dissolved substances (solutes) and
suspended particles, temperature gradients and fluctuations, and shrinkage and
swelling (van Breemen and Buurman 2002, pp. 15). Water content in the soil is
important because it demonstrates the feasibility of sustaining plant life. In coarse-
textured soils, water movement is particularly slow in non-saturated conditions.
Thus, water movement is dependent upon soil porosity. Results obtained by the LOI
test in 170 samples indicate a water content ranging from 0.05–5.62%, a mean of
0.83%, and a standard deviation of 0.80%. These values indicate very low moisture
contents in the samples to sustain plant life.
Premise 2. If the occupation surfaces are floors, samples will yield high Db values.
Ideally, the bulk density of a soil ranges between 1.10–1.60 g/cm3
Statistical values for Db of 142 analyzed samples range from 1.26 to
2.58, with a mean of 1.63. Porosity ranged from 2.8–52.5%. Based on
these values, it is possible to suggest that the structure and density of
the surface is not related to a natural soil.
Premise 3. If the habitation surfaces are floors, the samples are expected to have
low contents of organic matter and, if detected in large concentrations,
phosphorus was added by a different process. Organic matter is another
vital component of soil for plant growth since it contains essential
nutrients such as phosphorus (van Breemen and Buurman 2002). It also
influences soil structure, water holding capacity, nutrient contributions,
biological activity, water, and air infiltration rate. Results from the loss-
on-ignition (LOI) test indicate statistical values for organic matter
content ranged from 1.54% to 7.93% with a mean of 2.24% and a
standard deviation of 0.53% in the 169 samples (Table 1).
Carbonate (CaCO3) plays an important role in soil management, as its distribution
and quantity affects soil fertility, erosion, and available water capacity. The statistical
values obtained for CaCO3 in 170 samples ranged from 0.11–3.71% with a mean of
1.29%, and a standard deviation of 0.41% (Table 1).
Premise 4. If occupation surfaces are floors, pH and phosphorus concentrations
are expected to have high values. The statistical values of pH for the
172 analyzed samples range between 7.97 and 9.65 with a mean of
8.86 and a standard deviation of 0.26 (see Table 1). These values fit
Multivariate Spatial Analysis of Chemical Residues at a Hohokam Site 263
well with slightly to moderately calcareous soils. Values beyond 9.2 are
unexpected for this area.
Premise 5. If pH is low and organic matter and phosphates are high, then these
(organic matter and phosphates) have been added artificially.
The high concentration of phosphates in the sample was unreadable to the
spectrophotomer, so the solution had to be diluted tenfold (see Table 1 for
recalculated values). In the end, concentrations of phosphates range between 25.71
and 113.69 ppm (or milligram per kilogram) with a mean of 46.56 ppm.
Premise 6. If the surfaces of occupation are floors, then water content, salinity,
electrical conductivity, and organic matter should exhibit very low
The statistical values of electrical conductivity detected in the 172 analyzed
samples indicate a minimum value of 0.02 S/cm and a maximum of 0.57 S/cm
(Table 1). Most values concentrate in the low range as indicated by the mean 0.11 S/cm;
however, values greater than 0.30 S/cm are rather unusual, suggesting an analytical
discrepancy with the rest of the data.
Results from chemical analyses indicate poor conditions to sustain natural
vegetation, indicating that other processes influenced the chemical enrichment of
surfaces. The high values of bulk density are above the ideal levels for any soil,
leading us to suggest that the sampled area is an artificially created surface. LOI
values reveal a very low percentage of water in each sample, making plant growth
difficult. Consequently, the pH values are high in most samples due to a restricted
movement of water that would impede plant growth.
Table 1 Statistical Summary of Variables
Db Porosity EC TDS Water
N of cases 142 142 172 172 170
Minimum 1.260 2.800 0.020 0.010 0.050
Maximum 2.580 52.500 0.570 0.280 5.620
Mean 1.625 38.672 0.105 0.050 0.827
Standard deviation 0.210 7.916 0.078 0.038 0.797
Organic matter Carbonate pH Phosphates
N of cases 169 170 172 172
Minimum 1.540 0.110 7.970 25.710
Maximum 7.930 3.710 9.650 113.690
Mean 2.236 1.294 8.864 46.556
Standard deviation 0.530 0.412 0.256 15.868
N of cases 172
Standard deviation 0.634
264 López Varela and Dore
Some samples, however, show considerable amounts of organic matter and low
values of water contents. At the same time, the highest values for phosphates
distribute around pits and structures.
Based on these results, we can rule out our Premise 1 and suggest that the
surfaces under study could be regarded as archaeological floors. The determination
of carbonates in the samples and the high values of bulk density yield preliminary
evidence of a floor construction mixture based on sand. Knowing that the habitation
surfaces are floors, is an advantage for interpreting chemical residue results. At the
San Lucas site, the presence of fatty acids is low, but some features exhibit particular
concentrations that could be analyzed later by mass spectrometry. Despite the
limitations of this semiquantitative technique, it is providing a preliminary
assessment of its presence, and in the future, specific samples could be analyzed
with instrumental techniques.
We can assume that the identified chemical residues have a higher probability of
having been created by human activities, as the chemical enrichment developed on a
floor. In the absence of assigning a particular activity to a particular chemical
residue, one can still learn much about the structuring of human activities in space.
Even if different human activities simultaneously deposited trace amounts of
different chemical residues on the surface, their location can be discerned from the
spatial structuring of chemical data.
The Structuring of Chemical Data at San Lucas
In recent years, we have been exploring techniques that are rooted in satellite remote
sensing image analysis to better reflect the socialized use of space. These techniques
allow individual residue data sets to be combined and processed simultaneously, to
identify and tease out complex combinations of residues that may equate with sets of
actions (see Dore and López Varela, this volume). Although this might involve the
measurement and description of built and open spaces as they are revealed to us in
the present, the objective of their application is to understand the structure of
chemical data and the intensity of the use of space. To arrive to such an
understanding, we formulated a series of premises, following the ruled-based
Premise 7. If activity areas are differentiated on the basis of one chemical element
to identify discrete spatial areas, we could not rule out the enrichment
of natural soils from those of floors. Using multiple chemical elements
simultaneously to identify discrete spatial areas raises our analytic
ability to identify unique combinations or suites of chemical elements
in space. This may provide clues to the way space is socially used and
Thus, we created a raster surface for each variable (carbonates, phosphates,
organic matter, water, etc.) and rescaled values to 8-bit data space (0 to 255). To
reduce redundancy in the data, without sacrificing variability, we undertook a spatial
principal component analysis. With these techniques, we obtained three rasters that
retained 96.0% of the variability and allowed us to display the data set
Multivariate Spatial Analysis of Chemical Residues at a Hohokam Site 265
simultaneously in red, green, and blue (RGB) color space (Fig. 2). These methods
are identical to those described in more detail in the article by Dore and López
Varela in this volume.
While this colored raster composite is valuable to visualize spatial areas having
unique combinations of residues, it is limited in its ability to be quantified and to produce
secondary vector data sets of utility. It can, however, be used as a reference for an
unsupervised classification to ensure that a meaningful number of classes are obtained.
Classification is a discriminate technique used to partition space into areas having
similar characteristics of inputs, in this case, chemical residues. We used a neural
network-base classifier and through experiments with a number of classes, settled on 16
to approximate the principal component RGB (Red/Green/Blue) visualization (Fig. 3).
Proxy measures of activity intensity (frequency of repetition) and diversity (number of
actions) can be computed from the classification raster. Intensity can be calculated as
the frequency of polygon centroids in a given area (Fig. 4). Diversity can be calculated
as the number of different activities in a given area (Fig. 5).
Fig. 2 Display of the data set in RGB color space, after spatial principal component analysis (photograph
courtesy of Statistical Research, Inc. and modified by Christopher D. Dore)
266 López Varela and Dore
The resulting model is an estimate of the number of areas that could have been
represented in space, as we artificially created groups of unique residues that may
equate with unique sets of activities (Fig. 6). However, we can observe that (1) the
frequency of activities can be discussed relatively despite the fact that we don’t
know what these were in the past; (2) the relative amount of spatial area attributed to
these actions may be computed, and (3) the similarity, at least in terms of residue
output, may be examined with the dendrogram from the classification. With this
dendrogram, three major groups of related activities may be distinguished and that a
few pairs of activities are very closely related (Fig. 7). The main advantage of doing
this classification is its heuristic capacity to demonstrate that the structure of
chemical elements to architectural features is not a one-to-one correlation as most
studies suggest (Manzanilla 1996; Terry et al. 2004).
The spatial arrangement of the five excavated structures, open spaces, and pits at
the San Lucas site may be visible to us in the present as bounded (Fig. 8). The San
Lucas excavated data continues to be studied, including the analysis of artifacts.
Chronometric dating of archaeological data included archaeomagnetic studies.
Fig. 3 Neural network-base classifier based on 16 classes (illustration by Christopher D. Dore)
Multivariate Spatial Analysis of Chemical Residues at a Hohokam Site 267
Preliminary dating results that still need to be tied to other avenues of investigation
are suggesting that none of the structures were occupied at the same time (Deaver,
personal communication to Dore 2005). This is not the first time archaeomagnetic
dates suggest that two houses with associated work areas and trash deposits were not
occupied at the same time (Roth 2000). Adding structures to an existing settlement
may not always be behind population growth. These structures could have been
simply abandoned as the consequence of residential movement, resulting from a
socially negotiated process induced by the environment, ideology, conflict, and even
by health issues (Nelson and Schachner 2002).
This residential shifting is challenging to chemical analysis for interpretation of
space use. The sets of activities that we isolated with the classification may or may
not signal differential uses for these structures (Fig. 6). The perceived groupings of
unique residues could be related to similar activities involving different objects,
foods, or peoples. Differences in the structuring of the data could be related to the
Fig. 4 Proxy measures of activity intensity calculated as the frequency of polygon centroids in a given
area—blue (low) to red (high) (photograph courtesy of Statistical Research, Inc. and modified by
Christopher D. Dore)
268 López Varela and Dore
time when the activities took place. Although one could explore the function of a
structure based on the artifacts found on floors, the paucity of material data makes
this difficult (Eric Klucas, personal communication 2004). Artifacts left on floors,
particularly during abandonment, represent a fragment of time in the lives of past
people (Fig. 9). Despite the challenging issues residential shifting imposes to
interpretation, it is evident that spaces are constantly restructured to accommodate
the practice of everyday life.
The reflexive approach adopted for the analysis of chemical residues at the San
Lucas site, contrary to all expectations (Berggren and Hodder 2003), originates in
the world of applied archaeology. Chemical analysis is a potential tool to understand
Fig. 5 Proxy measures of activity diversity can be calculated as the number of different activities in a
given area—blue (low) to red (high) (photograph courtesy of Statistical Research, Inc. and modified by
Christopher D. Dore)
Multivariate Spatial Analysis of Chemical Residues at a Hohokam Site 269
the uses of space in applied or research contexts. Excavation strategies in the applied
sector might contradict research expectations. However, the study we have discussed
here demonstrates that chemical residues can be recovered as part of an applied
sector project, proving the impact of Luis Barba’s studies to this field of inquiry and
explaining why we decided to honor him with this publication.
Additionally, this particular setting has provided us with a unique opportunity to
assess the advantages and limitations of our current methodologies and theoretical
paradigms in soil analysis and interpretation. The approach has exposed the prob-
lematic issues for the interpretation of human activities and space use in the past.
Particularly, it has raised questions about the possibilities of recognizing the
individuality of space use and the ways we document time at multiple scales.
Archaeologists can no longer assume that the chemical residues recovered from
areas in which occupation is evident always correlate with human activities. Natural
factors also influence the deposition of chemical residues. This understanding is
means for the selection of analytical techniques both in the field and the laboratory
to recover and interpret chemical residues. But if we are to distinguish if a chemical
Fig. 6 Chemical-based “activity areas” within architectural structures. Colors correspond to unique
multivariate signatures across the suite of chemical elements analyzed (Illustration by Christopher D. Dore)
270 López Varela and Dore
Fig. 8 The spatial arrangement of the five excavated structures, open spaces, and pits, and chemical
sample area at San Lucas (illustration by Christopher D. Dore)
Fig. 7 The classification dendrogram shows that three major groups of related activities may be
distinguished ([8, 6, 4] [5, 9, 7, 11, 16, 3, 2, 10, 14, 15, 13] ). One also can see that a few pairs of
activities are very closely related ([7, 9] [11, 16] [13, 15]) [illustration by Christopher D. Dore]
Multivariate Spatial Analysis of Chemical Residues at a Hohokam Site 271
element is the result of human activity, we need first to move beyond the static
orientation introduced by those studies attempting to define the functionality of built
spaces based on the identification of a single activity. To a certain extent, this
orientation is further enhanced with the use of isopleths. For this study, modelling
the spatial structure of chemical data with satellite image analysis and spatial
statistics was useful to illustrate the dynamic use of space.
Second, archaeologists need to be cautious in their use of the ethnographic
context for the interpretation of human activities. The lives of those that are studied
in a modern context have changed through time, and the present is not a static
representation of the past. Ethnoarchaeological studies are helpful to investigate
what motivates the structuring of activities in space. In this regard, the structuring of
activities in space may be studied similar to the chaîne opératoire (Leroi-Gourhan
1943–1945) analytical concept of describing the sequences of steps by which natural
resources were transformed into meaningful and functional objects. Several scholars
(LaMotta and Schiffer 2001; Joyce and Lopiparo 2005) already have suggested
studying the chains of activities responsible for the formation of the archaeological
deposits. We are aware that this might be more difficult to recognize in
archaeological cases and that the approach we have introduced might not solve all
problems. However, we may be able to move from the experienced limitations for
the interpretation of chemical residues if we consider that the social logic of space is
leading to the chemical enrichment of surfaces.
Acknowledgements We would like to thank Dr. Eric Klucas, who managed the San Lucas project, for
his consideration of chemical analysis as a potential tool to define human activities at the site and for his
kindness in submitting our request to disseminate our research. Our special gratitude goes to project
Fig. 9 Artifacts left on floors particularly during abandonment represent a fragment of time in the live of
past peoples and these may not be representative of everything that happened in that space (photograph
courtesy of Statistical Research Inc.)
272 López Varela and Dore
sponsor Mr. Robert Zammit of BCIF for his openness and disposition to grant us permission to present and
publish the San Lucas chemical data at various scientific forums. We are grateful to Robert Heckman and
Drs. Jeffrey Homburg and Manuel Palacios-Fest for their support in collecting the samples in the field and for
sharing their inquisitive thoughts and observations that have extended the potential of this research beyond
our original expectations. With support of Mitch Eichsenseer and Jim Lofaro, we were able to process the
results of this investigation. We would like to thank all of the SRI staff for their support and enthusiasm,
particularly Dottie Ohman and Michelle Wienhold, in helping all of those who have worked in this project to
achieve our goals. López Varela would like to express special gratitude to Donn Grenda, Terry Majewski,
and Jeff and Debbie Altschul for supporting this investigation as part of my sabbatical year (2004–2005) at
Statistical Research Inc. Thanks to our anonymous reviewers for their insightful comments.
Appendix: Detailed Description of Test Procedures for Chemical Analyses
of Floor Samples
Manuel R. Palacios-Fest and Sandra L. López Varela
I. Bulk Density Determination by the Clod Method
1) Select 2–3 clods of soil of equal size and weight, whenever possible.
2) Tie a piece of thread, about 20 cm long, to each clod.
3) Weigh the bulk clod on an electronic balance, capable of reading 1/10,000 of a
gram and weighing suspended samples.
4) Record the weight in a log form.
5) Coat the clod with paraffin (density is 0.9) at approximately 60°C. Allow the
coating to dry. It is important that no holes are left uncoated. If bubbles appear,
repeat the coating several times to ensure that the sample is sealed. Then, weigh
the sample. One should be careful in not over coating the sample with paraffin,
as the excess may interfere with its weight in water.
6) Place a 1,000 ml beaker on a scale, with a specific volume of water that is to
remain constant for all the samples.
7) Suspend the coated sample and let it submerge into the beaker. Record the
weight. Be cautious in letting the clod hang at the same distance, to maintain a
constant error. If this is not followed, one can obtain different weight
measurements for the same clod, as this test is based on Archimedes’ principle.
8) Then assume the value of the density of water (1.00 g/cm3
) and estimate
porosity. The bulk density must be reported in milligram per cubic meter.
II. Loss on Ignition (LOI) to Estimate Contents of Water, Organic Matter,
and Carbonates with a Paragon Touch and Fire DTC 800 Furnace
This test requires the sieving of the sample to separate the gravel, through a 2-mm
sieve, from the fine fraction <2 mm. The use of gloves is recommended to avoid
adding grease, dust, or fat to the crucible. To obtain better results, the crucibles used
in this analysis after washing them, without soap, should be dried carefully to avoid
any water contents.
To determine the water content in the sample:
1) Control that porcelain crucibles are cleaned and marked with lead pencil.
2) Always use metal pliers when moving crucibles.
Multivariate Spatial Analysis of Chemical Residues at a Hohokam Site 273
3) Weigh every crucible and record its weight.
4) Add 1 g of sample to the crucible and record the new weight.
5) Place each crucible with 1 g of sample in drying oven at 105°C for 12 h or
6) Place hot crucibles in the desiccator for 30 min to cool the sample.
7) Weigh the crucibles that are now at temperature taken from desiccator.
8) Record the weight.
To determine the organic matter in the sample:
1) Control that porcelain crucibles continued to be marked with lead pencil after
their exposure to the dry oven.
2) Place the crucibles in the furnace by using metal pliers and/or gloves.
3) Turn the furnace ON.
4) Press Enter to Idle the furnace.
5) Press Ramp Hold and determine the user programming the kiln by setting a
6) Press Enter to set the time and temperature segments for heating and cooling
down the samples.
7) Choose 2 for two segments. The first one to set the heating temperature at 550°C
(RA 1) and the second one to set the cooling of the sample down to 105°C (RA2).
8) Press Enter to set the time of operation for those two segments: 4 h (Hold 1) at
550°C and 15 h (Hold 2) of cooling down at 105°C.
9) Press Enter twice to GO. An idle and dashed line will appear and the furnace
will start its operation.
10) After 15 h, the cooling process is complete and the samples can be removed
from the furnace and transferred into the desiccator for 30 min.
11) Weight the crucibles that are now at temperature taken from desiccator.
12) Record the weight.
To determine the total inorganic carbon (TIC) content in the sample:
1) Turn the furnace ON.
2) Press Enter to Idle the furnace.
3) Press Ramp Hold and determine the user programming the kiln by setting a
4) Press Enter to set the time and temperature segments for heating and cooling
down the samples.
5) Choose 2 for two segments. The first one to set the heating temperature at 900°C
(RA 1) and the second one to set the cooling of the sample down to 105°C (RA2).
6) Press Enter to set the time of operation for those two segments: 2 h (Hold 1) at
950°C and 20 h (Hold 2) of cooling down at 105°C.
7) Press Enter twice to GO. An idle and dashed line will appear and the furnace
will start its operation.
8) After 20 h, the cooling process is complete and the samples can be removed
from the furnace and placed into the desiccator.
9) Then weigh the crucible and record the measurement.
10) Discard the samples and wash crucibles with distilled water (no soap).
274 López Varela and Dore
III. Determination of pH, Electrical Conductivity, and Salinity
Measure pH, electrical conductivity (EC in mMhos/cm), and salinity (TDS [total
dissolved solids] in milligram per liter) using a pH meter with temperature control in
1:1 slurry of 10 g of sample and 10 ml of distilled water. Maintain lab room
temperature at (∼20°C).
Record pH measurements.
1) Calibrate pH meter using buffers (following manufacturers instructions).
2) Place 10 g of sample in small container.
3) Add 10 ml of distilled water.
4) Stir vigorously and let sit for 15 min.
5) Introduce pH meter electrode and read the value.
Record Conductivity and Salinity
1) Change the pH meter mode to EC and TDS to read conductivity and salinity,
2) Repeat measurement after a couple of minutes.
3) In between measurement, rinse the electrode with distilled water.
4) Record value in log worksheet.
Extractable Phosphate Procedure, using the Mehlich-II method
with a Hach Spectrophotometer
1) Weigh 2 g of <2-mm sample.
2) Place sample in a 60-ml plastic bottle.
3) Add 25 ml of 1:6 dilute Mehlich-II solution.
4) Mount in hollowed wooden tray and place tray in shaker for 10 min.
5) Prepare a set of containers with a funnel and filter paper to filter solution and
recover only the filtrate.
6) Prepare standards at 0.1, 0.5, and 1.0 mg/L of PO4 and blank (distilled water).
7) Enter Program 79 in the Hach spectrophotometer (follow manufacturer’s
8) Calibrate the Hach spectrophotometer to read PO4.
9) Label colorimeter vials with appropriate sample number.
10) Take 1 ml of filtered solution and place it in the vial.
11) Fill with distilled water to the 10 ml mark.
12) Add one pillow of PhosVer3 reagent and shake for 3–4 min.
13) Place vial in the Hach spectrophotometer chamber and read the value.
14) Repeat the reading after running the first batch.
15) Record values in log worksheet.
Fatty Acid Determination Test
1) Weigh 0.05 g of sample.
2) Place the sample in a beaker.
3) Carefully add 1 ml of chloroform.
Multivariate Spatial Analysis of Chemical Residues at a Hohokam Site 275
4) With metal pliers, agitate the sample.
5) Place the beaker on an alcohol burner until you obtain a concentrated solution.
6) Remove the beaker from the fire.
7) Add 10 ml of ammonium hydroxide (25%).
8) Add 2–3 drops of peroxide hydrogen.
9) Observe the formation of bubbles.
10) Determine the amount on a qualitative scale 0–3.
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