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  Z Morphol Anthropol 71:115–124; Steudel  Int J Primatol 2:81–90; Gingerich et al.  Am J Phys Anthropol 58:81–100; Conroy  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: email@example.com 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. 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