Journal of Archaeological Science 34 (2007) 804e813
http://www.elsevier.com/locate/jas
Paleodietary implications from stable carbon isotope analysis
of experimental cooking residues
John P. Hart a,*, William A. Lovis b, Janet K. Schulenberg c, Gerald R. Urquhart d
a
Research and Collections Division, New York State Museum, 3140 Cultural Education Center, Albany, NY 12230, USA
Department of Anthropology and MSU Museum, 354 Baker Hall, Michigan State University, East Lansing, MI 48824, USA
c
Division of Undergraduate Studies, 129 Grange Building, The Pennsylvania State University, University Park, PA 16801, USA
d
Lyman Briggs School of Science, E-194 Holmes Hall, Michigan State University, East Lansing, MI 48825, USA
b
Received 18 May 2006; received in revised form 24 August 2006; accepted 25 August 2006
Abstract
The regional timing of maize introduction in eastern North America is a long-standing topic of archaeological interest. Most recently, Morton
and Schwarcz [2004. Paleodietary implications from stable isotopic analysis of residues on prehistoric Ontario ceramics. Journal of Archaeological Science 31, 503e517] investigated the timing of maize introduction in Ontario through isotope analysis of charred cooking residues
adhering to the interior of prehistoric ceramic containers. They interpret their results to suggest maize was incorporated into diets after A.D.
600. We assess their approach and conclusions with stable carbon isotope assays on three sets of experimental cooking residues, evaluating
the variable combustion of carbon fractions, contributions of fats and carbohydrates, and the contribution of total carbon. We also undertake
multiple resource modeling of two part food mixes with green maize and maize flour. Our results suggest that systematic under representation
of maize can result depending on residue composition and that some prior knowledge of C3 plant and animal contents is necessary to interpret
stable carbon isotope values on cooking residues. We question the independent use of stable carbon isotope analysis of charred cooking residues
as a viable technique for extracting paleodietary information.
Ó 2006 Elsevier Ltd. All rights reserved.
Keywords: Prehistoric cooking residues; Carbon isotopes; Prehistoric cooking techniques
1. Introduction
The timing of maize’s (Zea mays ssp. mays) introduction
into various regions of eastern North America (ENA) and its
adoption as a dietary staple continue to be long-standing topics
of interest among archaeologists and paleoethnobotanists [17].
Various sources of information have been used to reconstruct
the histories of maize in ENA including direct AMS dates
on macrobotanical remains [4,6]; stable carbon isotope analysis of human bone [3,15], charred cooking residues [27,31,44],
and absorbed organic pottery residues [39e41]; pollen
* Corresponding author. Tel.: þ1 518 474 3895; fax: þ1 518 486 2034.
E-mail addresses: [email protected] (J.P. Hart), [email protected]
(W.A. Lovis), [email protected] (J.K. Schulenberg), [email protected] (G.R.
Urquhart).
0305-4403/$ - see front matter Ó 2006 Elsevier Ltd. All rights reserved.
doi:10.1016/j.jas.2006.08.006
recovered from sediments [10,55]; and phytoliths recovered
from cooking residues [19,47,48].
Recently, several studies have used stable carbon isotope
analysis of food residues from ceramic vessels to investigate
the adoption of maize in specific regions, and to investigate the
ways maize was incorporated into paleocuisine [31,39,44].
In the largest of these studies, Morton and Schwarcz [31]
investigated the timing of maize’s introduction in Ontario,
Canada using stable carbon isotope analysis of charred cooking residues adhering to the interiors of prehistoric pottery
sherds. Based on analysis of 137 residue samples from 50
components of 45 sites dating between approximately 680
B.C. and A.D. 1725, Morton and Schwarcz suggest that maize
was incorporated into diets after A.D. 600, consistent with isotopic evidence from human bone [23,45] and macrobotanical
evidence [6]. However, their results suggest only a small
J.P. Hart et al. / Journal of Archaeological Science 34 (2007) 804e813
.maize was apparently a minor ingredient in the mixtures
actually cooked in the pots. The remainder of dietary maize
must then have been consumed in different forms, either as
whole grains or cobs, or in some prepared form. Even if the
residues are an accumulation from many meals and therefore an average value of the food eaten, we cannot account
for their low mean d13C value given the clear evidence that
maize was a major food for the native peoples. [31, p. 515]
Morton and Schwarcz’s interpretations are based on a formula
used to estimate the percentage of C4 plants (PC4) that contributed to the creation of a residue. This formula assumes
a linear relationship between d13C and the proportion of
maize, the most likely C4 plant used in ENA, relative to C3
resource contribution to the residue.
In this article, we assess Morton and Schwarcz’s approach
by employing the results of stable carbon isotope assays on experimental cooking residues. We use the results from three independent experiments using 10% increments of maize and
wild rice (Zizania sp.) [19], maize and chenopodium (Chenopodium album) [44], and maize and white-tailed deer (Odocoileus virginianus) meat (reported here for the first time), to
assess the assumption of linearity between d13C and maize
proportions in charred, encrusted cooking residues. Our results
indicate that the relationship is not always linear, and as a result, the PC4 formula can substantially over- and underestimate maize proportions (see [25,35] for similar results in
animal tissues). We test three hypotheses that may account
for the patterning evident in the experimental residue d13C
values relative to maize proportions. Total carbon content of
the resources used in creating the experimental residues provides the best-fit for those patterns. We then assess the effectiveness of Morton and Schwarcz’s threshold for identifying
maize’s presence in a residue.
Our results suggest that prior knowledge of the C3 plants
and animals consumed on and cooked together at a site is necessary in order to interpret stable carbon isotope values on prehistoric charred cooking residues. The results also suggest the
importance of prior knowledge of food preparation and preservation techniques, especially whether green (wet) or mature
(dry) maize was cooked in the pot. In sum, we conclude that
d13C values on charred cooking residues cannot be used to
infer either presence of maize or its percent contribution to
a specific residue.
advocated caution in using bulk stable carbon isotope analysis
as the basis for interpreting the presence or absence of maize
in a residue. Similar to Morton and Schwarcz [31], Schulenberg [44] attempted to delineate a minimal isotopic threshold
for the presence of maize in archaeological residues. However,
her experimental results suggested that direct interpretation of
d13C is problematic. Hart et al. [19] combined d13C analysis
with phytolith analysis of charred cooking residues from an assemblage of central New York sherds. The results of this study
suggest that depleted d13C cannot be used to indicate the absence of maize in a residue; residues with depleted d13C contained phytolith assemblages identified as maize [19]. Morton
and Schwarcz’s [31] recent application of this technique to
a large sample of vessels from Ontario represents an important
effort to standardize the interpretation of d13C through a mathematical model.
Morton and Schwarcz [31] use the following formula to
estimate the amount of maize present in a residue:
PC4 ¼ ½ðds d3Þ=ðd4 d3Þ 100
ð1Þ
where d3 is the mean d13C for C3 plants (28&), d4 the mean
d13C for C4 plants (9&), and ds the d13C value for the residue. The formula assumes a linear relationship between the
proportion of maize contributing to a residue and the residue’s
d13C value. We obtained d13C on three series of experimental
residues with known proportions of maize and a second, C3
resource. The combined results allow us to test the underlying
assumption of linearity (Fig. 1).
In our assessment of the Morton and Schwarcz formula, it
was necessary to recognize several important aspects of their
work. They note, ‘‘the equation assumes that each sample is
a mixture of only C3 and C4 plants, whereas herbivore and
fish flesh were also present in the [prehistoric] diet’’ [31,
p. 508]. We attempt to directly address the impact of C3 herbivores in one of our experimental trials, although direct comparison with Morton and Schwarcz’s experimental data was
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30
40
50
60
70
80
90
100
-10
-15
13C
amount of maize was cooked in the vessels, even during
times when it is known that maize was a substantial dietary
component. Morton and Schwarcz [31] interpret the apparent
under-representation of maize in the cooking residues as an
indication that maize was processed in other ways:
805
-20
-25
-30
2. The PC4 formula
Two pilot studies in ENA investigated the applicability of
stable carbon isotope analysis to food residues [39,44]. While
these experimental applications varied in focus and technique
(Reber’s [39] focused on absorbed residues while Schulenberg’s [44] focused on encrusted residues), both researchers
-35
Percent Maize
Fig. 1. Comparison of experimental results with PC4 model. Plots of the experimental residues are based on the weight values in Table 1. (X ¼ deer meat and
maize flour, - and : ¼ wild rice and maize flour, B ¼ chenopodium and
frozen maize kernels.)
806
J.P. Hart et al. / Journal of Archaeological Science 34 (2007) 804e813
not possible because they do not specify proportions for the
residues made with more than one resource. They discuss
the potential impact of ‘‘variations within plant species and individual plants’’ [31, p. 508], although unlike our replications,
their experimental work only included the common bean (Phaseolus vulgaris) as a C3 plant [31, p. 513].
For our purposes, Morton and Schwarcz [31, p. 515] pose
a significant question about their results: ‘‘Why is there so little evidence of the presence of C4 plants. in these residues?’’. They argue that maize must have been a small
contributor to the meals cooked in pots. To explain the discrepancy between the isotope evidence from encrusted food
residues and those of measurement on human bones of the
same time periods, Morton and Schwarcz [31, p. 515] suggest
that maize was consumed primarily on the cob or as whole
kernels. The interpretation of the stable carbon isotope values
highlighted by this discrepancy is the central question to which
we directed our experimental data and analysis. We believe
our results provide a compelling alternative explanation to
the ones proposed by Morton and Schwarcz.
3. Materials and methods
Three series of experimental residues were created using
mixtures of maize with one other food source. In the first experiment, Schulenberg [44] used mixtures of supermarketpurchased frozen sweet corn and chenopodium (C. album)
harvested in southeastern New York to create a series of 11
residues. The experimental mixtures were done in 10% increments by weight. Whole chenopodium seeds and maize kernels were cooked in water in low-fired clay pots over coals.
The water was allowed to evaporate and the contents to
burn. The resulting charred material was then ground in a mortar with a pestle. Three subsamples of each residue were
submitted to Geochron Laboratories for carbon isotope assay.
The second experiment, conducted by Hart et al. [19], combined Iroquois White Flour maize, grown in New York by Jane
Mt Pleasant of Cornell University, and wild rice obtained from
a commercial vendor in Minnesota. Dried wild rice seeds and
maize kernels were ground separately into flour and sieved
through 1-mm mesh to remove any large particles. Eleven,
dry 1.25-ml mixtures were created in 10% increments by volume. These mixtures were simmered in 100 ml of water for
20 min with occasional stirring. The mixtures were then decanted into cans and placed on a wood fire. The water was allowed to evaporate and the mixture to burn. Two subsamples
of each residue were submitted to the Illinois State Geological
Survey (ISGS) Isotope Geochemistry Lab for carbon isotope
assay.
The third experiment, reported here for the first time, was
conducted by Lovis using lean white-tailed deer meat and Iroquois White Flour maize from the same batch used in experiment 2, albeit from a different ear. The deer meat came from
the upper peninsula of Michigan in a non-agricultural region
and where maize is not used as bait, thereby minimizing the
potential for C4 plant consumption. Isotopic analysis of prehistoric deer bone suggests maize was not a dietary component
of at least some deer populations [21,54] unlike modern deer
populations [5]. The same procedures were followed in this
experiment as related for experiment 2. The deer meat was frozen before grinding and then weighed prior to mixing. In order
to thoroughly mix the deer meat with the maize flour it was
necessary to place the mixtures in a blender. One subsample
of each mixture was submitted to ISGS for stable carbon
and nitrogen isotope assay.
During boiling and carbonization, the maize/meat mixture
separated into both ‘‘light’’ and ‘‘heavy’’ fractions. The former
was composed largely of separated plant material suspended in
a froth (probably high in starches/carbohydrates per Pierce [36,
p. 138]) and some fats, and the latter primarily of denser meat
particles. This resulted in carbonized residues in two locations:
at the upper part of the fluid line, and at the base of the container
(see Hastorf and DeNiro [20] for sampling of basal sherds). In
this experiment, the two residues were combined. In future research, it might be productive to sample each residue location
separately. It is possible that the locations from which residues
are drawn may affect isotope composition and therefore outcomes, i.e. it is expectable that basal residues may register
higher C3 content, and jar wall residues higher C4 content.
4. Results
Results of the d13C assays on the experimental residues are
presented in Table 1 and Fig. 1. Clearly, the underlying assumption of linearity in the PC4 formula is not realized by these results; the relationship between d13C and proportions of C3 and
C4 plants/consumers contribution to a residue in our experiments is distinctly nonlinear. The non-linearity varies depending
on the products used to create the samples. The maizeedeer residues produce a convex curve, while the maizeewild rice and
maizeechenopodium residues produce concave curves. The
maizeechenopodium curve is especially pronounced.
5. Modeling d13C
We tested three hypotheses to account for the nonlinear
relationship between maize proportions and d13C values:
1. Fractionation, or the uneven combustion of carbon isotopes where the reaction rates of the heavier 13C and lighter 12C differ, produces a nonlinear relationship between
the proportion of maize and the d13C values.
2. Different contributions of fats and carbohydrates (which
burn at different temperatures) to the residues create the
nonlinear relationship.
3. Uneven contribution of total carbon from each carbon
source creates the nonlinear relationship.
Fractionation of stable carbon isotopes is mass dependent
[14]. The square root of masses gives the fractionation ratio [14]:
rffiffiffiffiffiffiffi rffiffiffiffiffi
m13
13
Ratio ¼
¼
¼ 1:04
12
m12
ð2Þ
J.P. Hart et al. / Journal of Archaeological Science 34 (2007) 804e813
807
Table 1
Isotope results for experimental residues
Maize-wild rice
Maize-deer
13
13
13
Maize-chenopodium
% Maize (vol.)
% Maize (wt.)
d C-1
d C-2
d C-avg
% Maize (vol.)
% Maize (wt.)
d C
% Maize (wt.)
d13C
0
10
20
30
40
50
60
70
80
90
100
0
7.8
15.9
24.5
33.6
43.1
53.2
63.4
75.2
87.2
100
26.3
24.0
24.2
23.3
22.8
22.3
22.5
18.7
16.3
14.7
11.8
25.4
25.6
24.5
24.1
22.1
21.5
20.0
20.4
18.3
14.3
11.9
25.9
24.8
24.4
23.7
22.5
21.7
21.3
19.6
17.3
14.5
11.9
0
10
20
30
40
50
60
70
80
90
100
0
5.3
12.4
19.8
26.3
38.2
44.3
57.4
71.6
84.6
100
24.5
21.8
19.7
17.2
16.4
16.4
15.6
13.7
13.0
12.6
12.7
0
10
20
30
40
50
60
70
80
90
100
32.4
32.7
32.6
31.6
31.8
30.5
28.2
28.8
25.6
22.9
14.3
This means that 1.04 times as much of the original 13C compared to the original 12C remains in residues (relative to the
original amounts):
Ratio :
13Coriginal 13Cfinal 12Coriginal 12Cfinal
¼ 1:04
13Coriginal
12Coriginal
=
ð3Þ
As a result, fractionation results in a linear relationship, inconsistent with our experimental data. The hypothesis that fractionation affects the d13C ratios of the cooking residues can,
therefore, be rejected.
Fats and carbohydrates burn at different temperatures [9],
and as a result, higher proportions of the carbohydrates in
a food will char relative to the fats (lower burning temperature). However, to produce the curves resulting from our
experimental residues, there would need to be a large difference in the amount of fats vs. carbohydrates in the resources
used to create them. Percent fat and carbohydrate data for
the resources used in the experimental residues are presented
in Table 2. Deer has a much higher fat/carbohydrate ratio
than maize. This could have resulted in the heavier d13C
values even when maize is a low fraction (5% or 10% of
diet), producing the convex curve in Fig. 1. However, the chenopodium and wild rice fat/carbohydrate ratios are similar to
that of maize. The differences in the ratios between maize
and the other resources are not sufficient to produce the
Table 2
Overall carbon content of maize flour, green maize (kernels), chenopodium,
and deer meat
Maize flour
Green maize (kernels)
Chenopodium
Wild rice
Lean deer meatdfrozen
Fat
(%)
Carbohydrate
(%)
Protein
(%)
Percent of mass
from carbon
4.9
1.2
6.3
1.2
7.1
79.1
19.0
45.0
81.2
0.0
13.4
3.2
28.8
16.0
21.8
44.2
10.6
39.2
43.5
17.2
Fat, carbohydrate and protein values obtained from USDA Nutrient Database
figures, http://www.nal.usda.gov/fnic/foodcomp/search/. Percent of mass from
carbon calculated from formula carbon ¼ 0.80 (fat) þ 0.42 carbohydrate þ
0.53 protein.
13
strongly curved relationship shown in Fig. 1. As a result,
this hypothesis is also rejected.
To address the possibility that the total carbon in the various resources affected the d13C of the experimental residues,
we used percent of mass from carbon (from fats, carbohydrates, and protein) to calculate how much carbon each would
contribute if equal original weights were used to create the
mixtures. Fatty acid mass is w80% carbon [32], carbohydrate
mass w42% carbon, and protein mass w53% carbon [33]
(Table 3).
Percent of mass from carbon (%C) was calculated using
Eqs. (4) and (5); carbon contents for mixtures were calculated
using Eq. (6) (Table 3).
%CMaize ¼0:80FatMaize þ0:42CarbsMaize þ0:53ProteinMaize
ð4Þ
%COther ¼0:80FatOther þ0:42CarbsOther þ0:53ProteinOther
ð5Þ
where FatMaize, CarbsMaize and ProteinMaize are, respectively,
the grams of fat, carbohydrates and protein amounts per
100 g of maize. Frozen maize and maize flour had different
values. Similarly FatOther, CarbsOther and ProteinOther are the
fat, carbohydrates, and protein amounts per 100 g of the other
substance.
The combined mixtures’ d13CM values were calculated
from the following mixing equation [9]:
d13 CM
13
d CMaize ð%Maize %CMaize Þ þ d13 COther ð%Other %COther Þ
¼
ð6Þ
ð%Maize %CMaize Þ þ ð%Other %COther Þ
where %Maize is the percentage of maize in the mixture (0, 10,
20, . 100), %Other is the percentage of the other material in
the mixture (1 %Maize), %CMaize is the percentage of maize
Table 3
Biomolecules and their carbon content
Source
Biomolecule
% Carbon
Fatty acids
Carbohydrates
Proteins
CnHnO
C6H12O6
(ReCH(NH2)eCOOH)n
w80.0
42.0
53.0
J.P. Hart et al. / Journal of Archaeological Science 34 (2007) 804e813
by weight that is carbon (Eq. (4)), %COther is the percentage by
weight of the other that is carbon (Eq. (5)), d13CMaize is the initial d13C value for maize, and d13COther is the initial d13C value
for the other substance in the mixture.
For each model, we ran the equation using the observed
d13C values from the particular experiment to generate
a best-fit approximation (Fig. 2). The Green MaizeeChenopod
model used 13.7 for maize and 32.4 for chenopod; the
Maize FloureWild Rice model used 11.87 for maize and
26 for wild rice, and the Maize FloureDeer Meat model
used 12.6 for the maize and 24.49 for the deer meat.
The models also incorporate maximum and minimum d13C
values for the substances combined. Reported d13C values
for maize range from 8.7 to 15.7 [2,3,50], for chenopod
from 26 to 33.8 [43,44], for wild rice from 26 to
30.9, and for deer meat from 23 to 29.5 [49]. These
values created the outer bounds for our model.
Modeling the experiment using frozen maize and chenopodium, we find that maize kernels have high water content, resulting in a reduced amount of carbon (10.6%) relative to the
chenopodium (39.2%). Following Eq. (6), this difference in contribution of carbon to the residues produces a concave curvilinear relationship (Fig. 3). The model for the experiment that used
dry maize flour and dry wild rice flour had nearly equal amounts
of carbon in both substances. The carbon content of dry maize
flour is 44.2%, while dry wild rice flour contributes 43.5% carbon by weight (Table 3). This contribution produces a nearly linear relationship (Fig. 4). Finally, the model based on the dry
maize flour and frozen deer meat experiment produced a convex
curvilinear relationship because the carbon content of dry maize
flour is 44.2%, while frozen deer meat would contribute 17.2%
carbon by weight, (Table 3, Fig. 5).
In sum, the total carbon in resources used to create the experimental residues produces curves (Fig. 4) notably similar to
the curves derived for the experimental residues (Fig. 1). Departures of the experimental residue d13C values from the predicted values may reflect changes that occur during the
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Model
Minimum
Maximum
Observed
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Percent Maize
Fig. 3. Maximum, minimum, modeled and observed for wet/green maize and
chenopodium.
charring of vegetal matter as has been noted in laboratory experiments [37,51], or the loss of starches (carbohydrates) as a
consequence of poor heat control and boil over [36, p. 138]
among other uncontrolled variables. As a result, this hypothesis cannot be rejected.
To approximate more realistic situations where multiple
products would have been cooked in a single pot, we modeled
a slurry composed of one third each of deer, chenopodium and
wild rice. This slurry had a calculated d13CSlurry of 29.4, with
a minimum of 32.91 and maximum of 27.2 (Eq. (7)) and
carbon content of 33.3 g/100 g (Eq. (8)). Using Eq. (6) we calculated d13CM values for a mixture of the slurry with wet
0
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13C
808
100
0
10
20
30
40
50
60
70
80
90
100
Model
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Minimum
Maximum
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Observed
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13C
13C
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Percent Maize
13
-35
13
Fig. 2. Model d C values based on Eq. (6) and average C3 and C4 d C
values. (- ¼ wild rice and maize flour, : ¼ wild rice and wet maize,
B ¼ chenopodium and wet maize, X ¼ deer meat and maize flour.)
Percent Maize
Fig. 4. Maximum, minimum, modeled and observed for dry maize flour and
wild rice flour.
J.P. Hart et al. / Journal of Archaeological Science 34 (2007) 804e813
0
0
10
20
30
40
50
60
70
80
90
100
Model
-5
Minimum
Maximum
Observed
13C
-10
-15
-20
-25
-30
-35
Percent Maize
Fig. 5. Maximum, minimum, modeled and observed for dry maize flour and
deer meat.
(green) maize and maize flour, with maize ranging from 0% to
100% in 10% increments and slurry comprising the remainder.
for all but a few of the residues. Use of the PC4 formula to
identify the proportion of maize contributing to a prehistoric
cooking residue, then, is questionable without prior knowledge
of the C3 plants/consumers cooked in the pot, if maize was
also cooked, and if so whether the maize was cooked green
(wet) or mature (dry).
Morton and Schwarcz [31] use d13C values of 24& to
represent the presence of maize, and values <28&, to indicate no C4 plant contribution to the residue. Using an average
d13C value of 26& for industrial era C3 plants, results in
a threshold for determining a contribution of maize of
22& using the 4& offset suggested by Morton and
Schwarcz. The threshold, requires an approximate contribution of 35e55% maize in the maizeewild rice residues, approximately 5% for the deeremaize residues, and 90% for
the maizeechenopodium residues (Fig. 7). Given the varied
results of our experiments and models, which are dependent
on the mix of resources, any threshold chosen to determine
the presence of maize in charred residues is likely to result
in errors. These results further demonstrate the problematic
nature of the PC4 formula and its application and emphasize
the variation in d13C values depending on resources contributing to a residue.
13
d CDeer %CDeer þ d13 CChenopod %CChenopod þ d13 CWildRice %CWildRice
d CSlurry ¼
¼ 29:4
%CDeer þ %CChenopod þ %CWildRice
13
%CDeer þ %CChenopod þ %CWildRice
%CSlurry ¼
¼ 33:3
3
809
ð7Þ
7. Discussion
ð8Þ
The results of this modeling, which are also curvilinear, suggest that the d13C value of the residue depends heavily on
whether or not the maize used was green (wet) or mature
(dry) (Fig. 6).
6. Identifying maize in prehistoric cooking residues
The total amount of carbon contributed to a residue by
a resource, not strictly the proportion of the resource in
the food being cooked, determines the d13C value of the
residue. This means that the PC4 formula has the potential
to substantially under- or over-estimate the percentage of
maize in the food cooked in a pot. Because the direction
of the error depends on the nature of the food products contributing to the residue, there is no simple correction factor
for this problem.
The percent of maize contributing to the experimental residues is plotted against PC4 values in Fig. 1. In this figure, we
use industrial era average C3 and C4 d13C values of 26&
and 12&, respectively [26, p. 462]. As is evident, the PC4
formula significantly underestimates the percentage of maize
We recognize the complexity of the problem that we are
collectively addressing. Morton and Schwarcz’s attempt to
systematize the way in which we can interpret isotope values
from ceramic cooking residues particularly with respect to
maize content is a positive step in the process of addressing
the problem. However, the PC4 formula is based on the assumption that each resource present in a mixture contributes
carbon to the residues identical to that resource’s proportion
in the food being cooked. To the contrary, we expect different
resources to contribute different amounts of carbon because
they differ in carbon content and/or because they release different amounts of carbon during cooking that results in the
contribution to the residue (e.g., one resource breaks down
more quickly than another), or because they have been cooked
dried (e.g., matured and stored) or green. This means that at
least three sources of variation can potentially result in a broad
range of isotope combinations not accommodated by the PC4
formula. Our experimental data clearly demonstrate this, and
the results suggest that major interpretive errors related to
maize content may occur and are resource mix dependent.
As a result, Morton and Schwarcz’s threshold for maize
presence can potentially result in erroneous determinations
of maize’s contribution to cooking residues.
J.P. Hart et al. / Journal of Archaeological Science 34 (2007) 804e813
810
a) Dry Maize
0
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60
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100
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Minimum
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Maximum
13C
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13C
20
100
Model
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10
-5
-20
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Percent Maize
Fig. 7. Comparison of experimental values to a threshold for maize presence of
22&. Plots of the experimental residues are based on the weight values in
Table 1. (X ¼ deer meat and maize flour, - and : ¼ wild rice and maize
flours, B ¼ chenopodium and frozen maize kernels.)
Percent Maize
b) Green Maize
0
0
10
20
30
40
50
60
70
80
90
100
Model
-5
Minimum
Maximum
13C
-10
-15
-20
-25
-30
-35
Percent Maize
Fig. 6. Model d13C values of mixtures of hypothetical slurries of equal parts
deer, chenopod, and wild rice mixed with increments of (a) dry maize and
(b) green (wet) maize.
The most critical problem faced in the interpretation of
d13C values is the requirement for knowledge of what resources contributed to each residue formation (see also
[25,35]). This requires the generation of independent lines of
evidence beyond that of macrobotanical remains. Certainly,
macrobotanical remains can provide information about the
suite of resources potentially contributing to residues, but
unless embedded in residues, any given resource cannot be assumed to have contributed to that residue. Phytolith assemblages may provide more direct evidence of the botanical
content of residues, and have been found to be at odds with
data generated by analysis of macrobotanical remains [19,48].
This is clearly one avenue by which to clarify residue composition, although not all plants known to have been consumed
prehistorically in eastern North America produce phytoliths in
their consumable parts. Gas chromatographic methods to identify lipids can provide another source of information on both
plant and meat food sources at a site [8,28,38,40,41], although
resource specific identifications are not always possible.
Additional factors that need to be taken into account include the effects of charring or carbonization on isotopic fractionation. Heating and charring experiments of vegetal and
animal resources have shown that changes occur in bulk
d13C values [22,37,51]. In one study these changes ranged
from 0.5& to þ2.0& at varying temperatures for a single
resource [37] and in another from þ1.0& to 1.2& for varied
resources cooked together in a stew [22]. A third study showed
changes of up to 1& in plant cellulose following various cooking and charring procedures [29]. Although such changes may
not have significant affects on paleodietary isotopic analysis of
human bone [22,29], they probably account in part for the departures from expected of our experimental residues from the
models. Other experiments have shown a potential loss of
starches (carbohydrates) as a result of frothing and boil over
[36, p. 138]. The separation of fats from other carbon sources
during cooking may also result in depleted d13C values in residues formed on vessel necks and rims [27]. The various biochemical components of food resources may vary in their
carbon isotope values [50]. Differential preservation of these
components during charring may affect the isotope values of
residues, although one set of experiments suggested otherwise
[50]. This study [50] also found no statistically significant
difference between bulk and mass balance calculated carbon
isotope values using the isotope values for each biochemical
component. We have not systematically addressed these
issues.
There are also variations in d13C values in individual
plant species (see Table 4). The highly depleted d13C values
of the chenopodium used in Schulenberg’s [44] experiments,
J.P. Hart et al. / Journal of Archaeological Science 34 (2007) 804e813
811
Table 4
Variation in d13C values for selected prehistoric crop remains in eastern North America
Plant
d13C Range (&)
n
Source(s)
Sumpweed (Iva annua) seed
23.4 to 28.5
11
Squash (Cucurbita pepo) seed
Uncharred Squash (Cucurbita pepo) seed
24.9 to 26.4
23.6 to 26.6
3
4
Squash (Cucurbita pepo) rind
23.7 to 28.3
6
Bean (Phaseolus vulgaris) seed
Maize (Zea mays ssp. mays) kernel
Maize (Zea mays ssp. mays) cob
23.3 to 28.6
8.4 to 15.1
7.4 to 12.6
34
35
5
Gayle Fritz, personal communication, 2004a;
Mary J. Adair, personal communication, 2004b
Mary J. Adair, personal communication, 2004b
[34]; Monaghan, Lovis and Egan-Bruhy,
unpublished datac
Mary J. Adair, personal communication, 2004b;
Hart unpublished datad; Monaghan, Lovis and
Egan-Bruhy unpublished datac
[18]
[18,19,24,53]; Gayle Fritz, personal communication, 2004a
[18]
All samples are charred unless otherwise noted.
a
Values from Ozark rockshelters in Arkansas (see corresponding dates in [11]).
b
Values from various Great Plains sites (see corresponding dates in [1]).
c
Values from Michigan sites (see corresponding dates in [30]).
d
Value from Pennsylvania site (see corresponding date in [16]).
as well as those from the charred prehistoric residues of unknown composition reported by Lovis [27], suggest that the
range of d13C values must be broadened to incorporate such
variation. We have incorporated this information into our
models.
Such highly depleted values are normally associated with either forest floor materials or wetlands [52]. The physical
locations of archaeological sites as well as the habitats within
which plants such as chenopodium are found make such depleted d13C values more likely than not. Precontact archaeological sites are often situated adjacent to riverine or lacustrine
wetlands [7,42]. Furthermore, the disturbed soil situations in
which plants such as chenopodium thrive could well be found
on the margins of habitation site clearings rather than in the
habitation area itself, situations where forest or woodland soils
would be present, as well as on disturbed floodplain soils
[12,13,30]. We therefore suggest that modeling exercises must
reflect this range of variation.
If it were possible to identify all subsistence resources used
on a site as well as the habitats in which plant resources were
grown, the number of possible mixes of resources that may
have contributed to any given residue’s formation will be exceedingly large. These and other independent variables mean
that making inferences of paleodiet from stable carbon isotope
analysis of charred cooking residues is not at this time practicable. Additional experimentation taking all or some of these
variables into account is required to properly understand the
relationships between food source d13C values and those
obtained from charred cooking residues, and to make confident
dietary inferences from those values.
8. Conclusions
It is not possible to understand the relationships between
agriculture and socio-economic developments without a firm
understanding of crop histories. What has become increasingly
clear over the past decade is the need to develop and use multiple lines of evidence to build those crop histories [46].
Reliance on single sources of evidence can result in erroneous
conclusions about agricultural evolution and the roles played
by crops in subsistence systems. Continued refinement of
methods and techniques for identifying prehistoric food sources and their relative dietary contributions is critical. Morton
and Schwarcz’s attempt to standardize approaches to understanding d13C values from prehistoric cooking residues was
just such an attempt. However, the combined results of the
three experiments and the modeling summarized here indicate
that direct interpretation of d13C ratios to estimate the contribution of maize is not possible.
In reference to the results of their isotopic analysis of prehistoric cooking residues, Morton and Schwarcz [31, p. 515]
ask, ‘‘Why is there so little evidence of the presence of C4
plants. in these residues?’’ They suggest that maize was
probably a minor ingredient in the foods cooked in pots and
that rather, it must generally have been consumed as whole
grains or on the cob [31, p. 515]. Our results suggest that
the explanation probably lies in the nonlinear relationship between the proportion of maize cooked in a pot and the resultant d13C value of the residue. In order to interpret the d13C
value, prior knowledge of the resources cooked in the pot is
essential. Given this finding, it is unlikely that independent
use of stable carbon isotope analysis of charred cooking
residues is a viable technique for extracting paleodietary
information.
Acknowledgements
Obtaining deer meat with low or no C4 content posed a serious problem to our experiments. We thank Dr. George Cornell, Director of the MSU Native American Institute, for
putting us in touch with Kris and Dixie Stewart, proprietors
of the Toonerville Riverboat Tour, Soo Junction, MI. The
Stewarts provided us with appropriate samples of C3 consumer deer meat from Michigan’s Upper Peninsula. Funds
for the deeremaize and wild riceemaize carbon isotope assays were made available by the New York State Museum
812
J.P. Hart et al. / Journal of Archaeological Science 34 (2007) 804e813
and the New York State Biodiversity Research Institute.
Funding for the maizeechenopodium assays was from Geochron Research Awards and The Wenner Gren Foundation
(Grant #6606). Dr. Mark Schurr, Dr. Robert Feranec, and
Dr. Henry Schwarcz reviewed and provided many useful comments and suggestions on an earlier version of this paper.
Dr. Stanley Ambrose provided many insightful comments on
a version of the paper read by Lovis at the 2006 Society for
American Archaeology meeting. His comments helped us to
clarify a number of issues in this article. We appreciate our
colleagues’ insights. We also thank two anonymous reviewers
for their comments and suggestions.
References
[1] M.J. Adair, Great Plains paleoethnobotany, in: P.E. Minnis (Ed.), People
and Plants in Ancient Eastern North America, Smithsonian Books, Washington, DC, 2003, pp. 258e346.
[2] M. Bender, Mass spectrometric studies of carbon 13 variations in corn
and other grasses, Radiocarbon 10 (1968) 468e472.
[3] M. Bender, D.A. Barreis, R.L. Steventon, Further light on carbon isotopes and Hopewell agriculture, American Antiquity 46 (1981) 346e353.
[4] N. Conard, D.L. Asch, N.B. Asch, D. Elmore, H. Gove, M. Rubin,
J.A. Brown, M.D. Wiant, K.B. Farnsworth, T.G. Cook, Accelerator radiocarbon dating of evidence for prehistoric horticulture in Illinois, Nature
308 (1984) 443e446.
[5] A.B. Cormie, H. Schwarcz, Stable isotopes of nitrogen and carbon of
North American white-tailed deer and implications for paleodietary
and other food-web studies, Palaeogeography, Palaeoclimatology, Palaeoecology 107 (1994) 227e241.
[6] G.W. Crawford, D.G. Smith, V.E. Bowyer, Dating the entry of corn (Zea
mays) into the lower Great Lakes, American Antiquity 62 (1997) 112e
119.
[7] G.W. Crawford, D.G. Smith, J.R. Desloges, A.M. Davis, Floodplains and
agricultural origins: a case study in south-central Ontario, Canada, Journal of Field Archaeology 25 (1998) 123e137.
[8] J.W. Eerkens, GCeMS analysis of fatty acid ratios of archaeological potsherds from the Western Great Basin of North America, Archaeometry
47 (2005) 83e103.
[9] R.P. Evershed, C. Heron, S. Charters, L.J. Goad, The survival of food residues: new methods of analysis, interpretation and application, in:
A.M. Pollard (Ed.), New Developments in Archaeological Science.
Proceedings of the British Academy 77, Oxford University Press,
Oxford, 1992, pp. 187e208.
[10] M.L. Fearn, K. Liu, Maize pollen of 3500 B.P. from southern Alabama,
American Antiquity 60 (1995) 109e117.
[11] G.J. Fritz, Prehistoric Ozark Agriculture: The University of Arkansas
Rockshelter Collections, U.M.I. Dissertation Service, University of North
Carolina at Chapel Hill, Ann Arbor, MI, 1986.
[12] J.P. Gallagher, R.F. Boszhart, R.F. Sasso, K. Stevenson, Oneota ridged
field agriculture in Southwestern Wisconsin, American Antiquity 50
(1985) 605e612.
[13] J.P. Gallagher, R.F. Boszhart, R.F. Sasso, K. Stevenson, Floodplain agriculture in the driftless area: a reply to Overstreet, American Antiquity 52
(1987) 398e404.
[14] K. Habfast, Fractionation in thermal ionization source, International
Journal of Mass Spectrometry and Ion Processes 51 (1983) 165e189.
[15] R.G. Harrison, M.A. Katzenberg, Paleodiet studies using stable carbon
isotopes from bone apatite and collagen: examples from Southern Ontario and San Nicolas Island, California, Journal of Anthropological Archaeology 22 (2003) 227e244.
[16] J.P. Hart, N.A. Sidell, Additional evidence for early cucurbit use in the
northern Eastern Woodlands east of the Allegheny Front, American Antiquity 62 (1997) 523e537.
[17] J.P. Hart, Maize agriculture evolution in the eastern woodlands of North
America: a Darwinian perspective, Journal of Archaeological Method
and Theory 6 (1999) 137e180.
[18] J.P. Hart, D.L. Asch, C.M. Scarry, G.W. Crawford, The age of the common bean (Phaseolus vulgaris L.) in the Northern Eastern Woodlands of
North America, Antiquity 76 (2002) 377e385.
[19] J.P. Hart, R.G. Thompson, H.J. Brumbach, Phytolith evidence for early
maize (Zea mays) in the northern Finger Lakes region of New York,
American Antiquity 68 (2003) 619e640.
[20] C. Hastorf, M.J. DeNiro, Reconstruction of prehistoric plant production and cooking practices by a new isotopic method, Nature 315
(1985) 489e491.
[21] M.A. Katzenberg, Stable isotope analysis of archaeological faunal
remains from Southern Ontario, Journal of Archaeological Science 16
(1989) 319e329.
[22] M.A. Katzenberg, S.R. Saunders, S. Abonyi, Bone chemistry, food, and
history: a case study from 19th century upper Canada, in: S.H. Ambrose,
M.A. Katzenberg (Eds.), Biogeochemical Approaches to Paleodietary
Analysis, Kluwer Academic/Plenum Publishers, New York, 2000, pp.
1e22.
[23] M.A. Katzenberg, H.P. Schwarcz, M. Knyf, F.J. Melbye, Stable isotope
evidence for maize horticulture and paleodiet in southern Ontario, Canada, American Antiquity 60 (1995) 335e350.
[24] T.D. Knapp, Pits, plants, and place: recognizing late prehistoric subsistence and settlement diversity in the Upper Susquehanna drainage, in:
J.P. Hart, C.B. Rieth (Eds.), Northeast Subsistence-Settlement Change
A.D. 700e1300, New York State Museum Bulletin 496, University of
the State of New York, Albany, 2002.
[25] P.L. Koch, D.L. Phillips, Incorporating concentration dependence in stable isotope mixing models: a reply to Robbins Hilderband and Farley,
Oecologia 133 (2002) 14e18.
[26] M.J. Kohn, T.E. Cerling, Stable isotope compositions of biological
apatite, Reviews in Mineralogy and Geochemistry 48 (2002) 455e488.
[27] W.A. Lovis, Curatorial considerations for systematic research collections: AMS dating of a curated ceramic assemblage, American Antiquity
55 (1990) 382e387.
[28] M.E. Malainey, R. Przybylski, B.L. Sherriff, The fatty acid composition
of native food plants and animals of western Canada, Journal of Archaeological Science 26 (1999) 83e94.
[29] B.D. Marino, M.J. DeNiro, Isotopic analysis of archaeobotanicals to reconstruct past climates: effects of activities associated with food preparation on carbon, hydrogen and oxygen isotope ratios of plant cellulose,
Journal of Archaeological Science 14 (1987) 537e548.
[30] G.W. Monaghan, W.A. Lovis, K.C. Egan-Bruhy, Earliest cucurbita in the
Great Lakes region USA, Quaternary Research: An Interdisciplinary
Journal 65 (2006) 216e222.
[31] J.D. Morton, H. Schwarcz, Paleodietary implications from stable isotopic
analysis of residues on prehistoric Ontario ceramics, Journal of Archaeological Science 31 (2004) 503e517.
[32] A.E. Needham, The Uniqueness of Biological Materials, Pergamon
Press, Oxford, 1965.
[33] D.M. O’Brien, D.P. Schrag, C.M. del Rio, Allocation to reproduction in
a hawkmoth: a quantitative analysis using stable carbon isotopes, Ecology 81 (2000) 2822e2831.
[34] B.E. Perkle, Cucurbita pepo from King Coulee, southeastern Minnesota,
American Antiquity 63 (1998) 279e288.
[35] D.L. Phillips, P.L. Koch, Incorporating concentration dependence in stable isotope models, Oecologia 130 (2002) 114e125.
[36] C. Pierce, Reverse engineering the ceramic cooking pot: cost and performance properties of plain and textured vessels, Journal of Archaeological
Method and Theory 12 (2005) 117e157.
[37] I. Poole, F. Braadbaart, J.J. Boon, P.F. van Bergen, Stable carbon isotope
changes during artificial charring of propagules, Organic Geochemistry
33 (2002) 1675e1681.
[38] J.M. Quigg, M.E. Malainey, R. Przybylski, G. Monks, No bones about it:
using lipid analysis of burned rock and groundstone residues to examine
Late Archaic subsistence practices in South Texas, Plains Anthropologist
46 (2001) 283e303.
J.P. Hart et al. / Journal of Archaeological Science 34 (2007) 804e813
[39] E.A. Reber, Maize detection in absorbed pottery residues: development
and archaeological application, Department of Anthropology, Harvard
University, Cambridge, MA, 2001.
[40] E.A. Reber, S.N. Dudd, N.J. van der Merwe, R.P. Evershed, Direct detection of maize in pottery residues via compound specific stable carbon isotope analysis, Antiquity 78 (2004) 682e691.
[41] E.A. Reber, R.P. Evershed, How did Mississippians prepare maize? The
application of compound-specific carbon isotope analysis to absorbed
pottery residues from several Mississippi Valley sites, Archaeometry
46 (2004) 19e33.
[42] R.F. Sasso, La Crosse region Oneota adaptations: changing late prehistoric subsistence and settlement patterns in the Upper Mississippi Valley,
Wisconsin Archaeologist 74 (1993) 324e369.
[43] M.J. Schoeninger, Reconstructing prehistoric human diet, in: T.D. Price
(Ed.), The Chemistry of Prehistoric Human Bone, Cambridge University
Press, Cambridge, 1989, pp. 38e67.
[44] J.K. Schulenberg, The Point Peninsula to Owasco transition in central
New York, Department of Anthropology, The Pennsylvania State University, University Park, PA, 2002.
[45] H.P. Schwarcz, J. Melbye, M.A. Katzenberg, M. Knyf, Stable isotopes in
human skeletons of southern Ontario: reconstructing paleodiet, Journal of
Archaeological Science 12 (1985) 187e206.
[46] J. Smalley, M. Blake, Stalk sugar and the domestication of maize,
Current Anthropology 44 (2003) 675e703.
813
[47] R.G. Thompson, R.A. Kluth, D.W. Kluth, Tracing the use of Brainerd
Ware through opal phytolith analysis of food residues, Minnesota
Archaeologist 53 (1994) 86e95.
[48] R.G. Thompson, J.P. Hart, H.J. Brumbach, R. Lusteck, Phytolith
evidence for twentieth-century B.P. maize in northern Iroquoia, Northeast
Anthropology 68 (2004) 25e40.
[49] L.L. Tieszen, T.W. Boutton, K.G. Tesdahl, N.A. Slade, Fractionation and
turnover of stable carbon isotopes in animal tissues: implications for
d13c analysis of diet, Oecologia (Berlin) 57 (1983) 32e37.
[50] L.L. Tieszen, T. Fagre, Carbon isotopic variability in modern and
archaeological maize, Journal of Archaeological Science 20 (1993)
25e40.
[51] C.S.M. Turney, D. Wheeler, A.R. Chivas, Carbon isotope fractionation
in wood during carbonation, Geochemica et Cosmochimica Acta 70
(2006) 960e964.
[52] N.J. van der Merwe, Carbon isotopes, photosynthesis, and archaeology,
American Scientist 70 (1982) 596e606.
[53] G.E. Wagner, Uses of plants by the Fort Ancient Indians, U.M.I. Dissertation Services, Washington University, Ann Arbor, MI, 1987.
[54] C.D. White, H.P. Schwarcz, Ancient Maya diet at Lamanai, Belize: as
inferred from isotopic and chemical analysis of human bone, Journal
of Archaeological Science 16 (1989) 451e474.
[55] D.R. Whitehead, Prehistoric maize in southeastern Virginia, Science 150
(1965) 881e883.