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Craniodental body mass estimators in the dwarf bushbaby (Galagoides).

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AMERICAN JOURNAL OF PHYSICAL ANTHROPOLOGY 115:187–190 (2001)
Craniodental Body Mass Estimators in the Dwarf
Bushbaby (Galagoides)
Frank P. Cuozzo*
Social Sciences Division, Las Positas College, Livermore, California 94550
KEY WORDS
dwarf galagos; body mass estimation; individual variation
ABSTRACT
This study reports data on 17 craniodental body mass estimators in a sample (n ⫽ 38) of dwarf
galagos (Galagoides). Correlation coefficients (r) range
from a high of 0.64 for bizygomatic breadth and body mass
to a low of 0.10 for M3 length and body mass. Of the 17
variables studied, 7 exhibit significant (P ⬍ 0.05) correlation coefficients, with 5 of the 7 being multitooth (i.e.,
tooth row) or cranial variables. In contrast to the correlation coefficients of greater than 0.90 (e.g., Martin [1980] Z
Morphol Anthropol 71:115–124; Steudel [1981] Int J Primatol 2:81–90; Gingerich et al. [1982] Am J Phys Anthropol 58:81–100; Conroy [1987] Int J Primatol 8:115–
137) published for higher taxonomic level analyses (i.e.,
all-primate or prosimian) for many of the same variables
studied here, the current data indicate weaker relation-
Body size is generally recognized as a key indicator of mammalian ecology and adaptation. Characteristics such as life history (Calder, 1984; Iskajer et
al., 1989; Harvey and Nee, 1991), diet (Kay and
Covert, 1984), and locomotion (Preuschoft et al.,
1998; Fleagle, 1999) exhibit strong correlations with
body size. Therefore, knowledge of an animal’s body
size alone can eliminate many of the possible physiological and behavioral combinations exhibited by
that animal, such as type of diet and mode of locomotion (McNab, 1990). This has great utility for the
study of fossil mammals in that many characteristics of an extinct animal’s adaptive profile can be
elucidated based on knowledge of its body size. As a
result, body size scaling in extant animals and the
estimation of body size among extinct forms have
received much attention in primate evolutionary biology (e.g., Kay, 1975; Fleagle, 1978; Martin, 1980;
Steudel, 1981; Gingerich, 1981; Gingerich et al.,
1982; Jungers, 1985; Conroy, 1987; Dagosto and
Terranova, 1992; Payseur et al., 1999).
Many studies of mammalian body size use body
mass as a surrogate measure (Iskajer et al., 1989).
Most studies of body size estimation have therefore
focused on relationships between body mass and
selected cranial, dental, and postcranial variables.
These relationships are usually discussed in terms
of correlation coefficients and linear regressions
computed at the ordinal, subordinal, or familial level
(e.g., Gingerich et al., 1982; Conroy, 1987; Dagosto
©
2001 WILEY-LISS, INC.
ships when analyzed at the generic level. Possible explanations for the contrast in correlation coefficients between
the current and many previous studies include the following: 1) individual variation due to a geographically dispersed sample, 2) individual body mass fluctuations due to
seasonal food availability, and 3) individual variation
within the sample due to variation in life-history parameters. Because the overall size range of the individuals in
a specific or generic level analysis is smaller than that in
an ordinal or subordinal sample, the individual variation
normally masked when using species means represents a
larger proportion of the total variation in a more limited
sample. This may then be a cause of these weaker correlations. Am J Phys Anthropol 115:187–190, 2001.
©
2001 Wiley-Liss, Inc.
and Terranova, 1992). Those studies addressing relationships at lower taxonomic levels (see references
in Conroy, 1987) have been limited primarily to anthropoid primates. The tarsioid regression of Gingerich (1981), based in part on extant tarsiers, is one
notable exception. More recent studies addressing
lower level taxonomic groups have continued to focus on anthropoid body mass, including Harrison
(1989) and Zambon et al. (1999), both of which used
body mass regressions for Cercopithecus aethiops to
estimate body mass in the extinct ceropithecoid Victoriapithecus. There remains, however, a paucity of
data on body mass relationships at lower taxonomic
levels (i.e., specific or generic) among small-bodied
prosimians. One reason for this is that there are few
prosimian samples available that include a sufficient number of specimens with an associated body
mass. Here I present data on the relationship between body mass and selected craniodental variGrant sponsor: University of Colorado Department of Anthropology
Predissertation Grant; Grant sponsor: University of Colorado Museum William H. Burt Grant; Grant sponsor: Beverly Sears Dean’s
Small Grant, Graduate School at University of Colorado-Boulder.
*Correspondence to: Frank P. Cuozzo, Social Sciences Division, Las
Positas College, 3033 Collier Canyon Road, Livermore, CA 94550.
E-mail: fcuozzo@clpccd.cc.ca.us
Received 29 October 1999; accepted 2 February 2001.
188
F.P. CUOZZO
1
TABLE 3. Correlation coefficients (r) and coefficients of
determination (r2) for each variable and body mass1
TABLE 1. Nation of origin of specimens studied
Nation
Number of specimens
Benin
Central African Republic
Democratic Republic of Congo
Ghana
Ivory Coast
Liberia
Nigeria
Togo
3
2
1
12
10
2
4
4
1
Nations listed in alphabetical order.
TABLE 2. Craniodental variables used in this study
Abbreviation
CL
ZYG
PAL
MAXTR
MANTR
P4L
M1L
M2L
M3L
M1L ⫻ W
M2L ⫻ W
P4L
M1L
M2L
M3L
M1L ⫻ W
M2L ⫻ W
Variable
Maximum length of cranium
Bizygomatic breadth
Palate breadth measured at M3
Maxillary tooth row length from C to M3
Mandibular tooth row length from P2 to M3
Fourth upper premolar length
First upper molar length
Second upper molar length
Third upper molar length
First upper molar length ⫻ width
Second upper molar length ⫻ width
Fourth lower premolar length
First lower molar length
Second lower molar length
Third lower molar length
First lower molar length ⫻ width
Second lower molar length ⫻ width
ables in a sample of dwarf galagos (genus Galagoides, but see below) with known individual body
masses.
MATERIALS AND METHODS
Data were collected from 38 dwarf galago skeletal
specimens housed in the Departments of Mammalogy at the United States National Museum of Natural History and the American Museum of Natural
History. Only adult, wild-caught specimens of
known body mass were studied. Body mass data
were collected from specimen tags and, when possible, verified in collection catalogs. Adult status was
determined based on dental eruption; only those
specimens exhibiting a fully erupted permanent
dentition were included. All specimens were collected in equatorial western and central Africa (Table 1), and only specimens with locality data were
studied. Seventeen craniodental variables were analyzed (Table 2), with all measurements collected
using Fowler digital needle-point calipers, measured
to the nearest 0.01 mm. Because postcranial material was available for only a small number (⬍5) of
these specimens, the current study is limited to
craniodental variables. As these specimens exhibited varying degrees of preservation, not all measurements were available for each specimen. All
measurements were converted to natural logarithms (loge) prior to statistical analyses. Correlation coefficients (r) and coefficients of determination
(r2) were then computed for each of the 17 cranio-
Variable2
n
r
r2
CL
ZYG
PAL
MAXTR
MANTR
P4L
M1L
M2L
M3L
M1L ⫻ W
M2L ⫻ W
P 4L
M1L
M2L
M3L
M1L ⫻ W
M2L ⫻ W
29
25
25
32
30
36
36
36
37
36
35
35
35
35
33
35
34
0.47**
0.64**
0.43**
0.47**
0.32*
0.20
0.24
0.35*
0.31*
0.12
0.23
0.18
0.17
0.11
0.10
0.11
0.22
0.22
0.41
0.19
0.22
0.10
0.04
0.06
0.12
0.10
0.01
0.05
0.03
0.03
0.01
0.01
0.01
0.05
1
Single asterisk denotes significant correlation coefficient (r) at
P ⫽ 0.05; two asterisks denote significant correlation coefficient
(r) at P ⫽ 0.01.
2
See Table 2 for variable definitions.
dental variables and body mass, and correlation coefficients were tested for significance at the 0.05 and
0.01 levels.
Although all specimens in this sample are identified as Galagoides demidoff, I prefer to view this
data set at the generic level for the following reasons. First, recent taxonomic revisions of the dwarf
galagos (e.g., Bearder et al., 1995; Honess, 1996;
Bearder, 1999) indicate greater specific diversity
within the genus Galagoides, and Honess (1996)
suggests that the “demidoff” group may in fact consist of more than one species. Second, G. demidoff
and G. thomasi are known to be sympatric in many
areas of equatorial western Africa (Wickings et al.,
1998; Bearder, 1999), with vocalization pattern and
genital morphology among their distinguishing features. Although it is likely that this sample is made
up largely, if not completely, of G. demidoff specimens, it is possible that several G. thomasi individuals or specimens from another as yet unnamed
species are included in this sample. In light of these
constraints, I choose to err on the side of caution and
view these data as a generic data set. I follow the
classification by Honess (1996), in which Galagoides
includes only the various forms of dwarf galago, and
not Allen’s Galago (Galago alleni).
RESULTS AND DISCUSSION
Table 3 shows the correlation coefficients (r) and
coefficients of determination (r2) for each of the 17
craniodental variables and body mass. Correlation
coefficients range from a high of 0.64 for bizygomatic
breadth (r2 ⫽ 0.41, n ⫽ 29) to a low of 0.10 for M3
length (r2 ⫽ 0.01, n ⫽ 33). Of the 17 correlation
coefficients, 7 are significant at the 0.05 level, with 4
of the 7 also significant at the 0.01 level. Also of
interest is that, of the 7 significant values, only 2
represent single-tooth variables (M2 and M3 length),
GALAGOIDES BODY MASS ESTIMATORS
with the remaining 5 being either multitooth (i.e.,
tooth row) or cranial variables. The relationships
revealed by the current analysis are lower than
those reported in previous studies conducted at
higher taxonomic levels (all-primate or prosimian),
in which correlation coefficients were often greater
than 0.90 for many of the same craniodental variables analyzed here (e.g., Martin, 1980; Steudel,
1981; Gingerich et al., 1982; Conroy, 1987). For example, the strongest relationship with body mass in
this study is exhibited by bizygomatic breadth (r ⫽
0.64, r2 ⫽ 0.41, n ⫽ 25, significant at 0.01). In
contrast, both Martin (1980) and Steudel (1981) reported a correlation coefficient of 0.98 (r2 ⫽ 0.96) for
the same variable. Also in contrast to previous studies, in which molar area correlation coefficients of
greater than 0.95 were reported for all-primate analyses (e.g., Gingerich et al., 1982; Conroy, 1987), none
of the molar area variables in the current study (see
Table 3) exhibited a significant relationship with
body mass. For example, in the current study, the
correlation coefficient for M1 area (r ⫽ 0.11, r2 ⫽
0.01, n ⫽ 35, not significant) is far lower than the
0.967 reported by Gingerich et al. (1982) and the
0.96 reported by Conroy (1987). Therefore, the current data support previous comments (e.g., Steudel,
1981; Conroy, 1987) that body mass scaling relationships are weak at lower taxonomic levels. This study
indicates that this is especially true for dental variables, in which only 2 of the 12 correlations are
significant at the 0.05 level, with none exhibiting a
correlation coefficient of greater than 0.35 (M2
length).
There are several possible reasons for the contrast
in correlation coefficients between the current study
and previously published values. First, geographic
variation may be a source of these lower correlation
coefficients. This sample is geographically dispersed, with individual specimens originating from
a wide area in equatorial western and central Africa,
a region of several thousand square miles (see Table
1). Second, the dwarf galagos in this sample were
collected from a region with marked seasonality and
periods of differential food availability (Charles-Dominique, 1977; Wickings et al., 1998). In small-bodied primates, seasonal differences in food availability can result in large individual body mass
fluctuations. For example, mouse lemurs exhibit up
to a 30% deviation in individual body mass during
the year (e.g., Fietz, 1998). Because these specimens
were collected at different times of the year, seasonal food availability may be a source of individual
body mass variation. Finally, the variation in this
sample could be a result of individual life-history
variation. Reproductive status (pregnant or lactating), general health (nutrition level or disease), or
level of maturity (young adult vs. old adult) could all
influence the body mass of an individual.
Any of the above variables could have had an
effect on the composition of this sample. Although
hard-tissue measurements such as bizygomatic
189
breadth or tooth size will not fluctuate during the
year or during an individual’s adult life due to the
above factors, correlation coefficients will vary with
subsequent changes in individual body mass. Therefore, each or all of these possible sources of individual variation could have had an effect on the statistical relationships revealed in this lower level
taxonomic analysis. Conroy (1998) commented on
this idea, noting that because an animal’s body mass
will often vary during its lifetime (often dramatically since eruption of the adult dentition), it should
not be a surprise that intraspecific body mass correlations are lower than are those for interspecific
samples. Because the overall size range of the specimens in this study is smaller than that in higher
taxonomic level analyses, measurement errors or
small fluctuations such as those addressed above
represent a larger portion of the total variation
(Iskajer et al., 1989). This may then be a cause of
these lower correlations.
Because there are few prosimian samples with
associated individual body masses (Jungers, 1985;
Dagosto and Terranova, 1987), it is difficult to conclude if the source of the contrast between the data
presented here and previous studies is a result of the
above variables. Only through cross-taxonomic comparative study will we be able to determine whether
the lower body mass correlations in more limited
taxonomic samples are a result of sampling error
due to individual variation, or if they reflect a larger
theoretical issue concerning scaling relationships.
For example, the authors of one recent study (Kozlowski and Weiner, 1997; reviewed in Norris, 1998)
argued that interspecific allometries are incidental
statistical patterns resulting from body-size optimization. With the tremendous increase in field studies on prosimians in recent years, data sets for
which the possible sources of variation listed earlier
can be controlled (e.g., Sauther et al., 1999) may not
be as difficult to obtain as in the past. Only through
the comparison of such controlled data sets we will
be able to test the above ideas.
ACKNOWLEDGMENTS
I thank Dr. Bert Covert, Dr. Michelle Sauther,
and Dr. Ann Magennis, as well as the AJPA editor
and two anonymous reviewers, for helpful comments
on this manuscript. I thank Dr. R. MacPhee (American Museum of Natural History, New York, NY)
and Dr. R. Thorington (United States National Museum of Natural History, Washington, DC) for permitting access to the specimens in their care. I also
acknowledge the curatorial staffs at these institutions for their assistance.
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