Tooth size and metabolic requirements in Primates: The 'equivalence between exponents' under discussion
The functional significance of teeth size, specifically postcanine tooth size has contributed a vast amount of scientific literature. Nevertheless, these studies have been based on 'equivalence between exponents'. That is, when the tooth size scales to the 0.75 power of body size exponent...
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| Lenguaje: | English |
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Sociedad Chilena de Anatomía
2013
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| Acceso en línea: | http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0717-95022013000400008 |
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| Sumario: | The functional significance of teeth size, specifically postcanine tooth size has contributed a vast amount of scientific literature. Nevertheless, these studies have been based on 'equivalence between exponents'. That is, when the tooth size scales to the 0.75 power of body size exponent is interpreted as reflecting differences in metabolic requirements. On the contrary, if the obtained exponent is close to isometry, such slope is interpreted as that variation in teeth size is an incidental consequence of body size variation. In this paper, we show the results of a study in which the relationship between postcanine tooth occlusal area (PCOA) and basal metabolic rate (BMR) has been evaluated in 28 primate species. On one hand, the results obtained indicate that there is a high correlation between the BMR and the size of the PCOA, even when phylogenetic control tests are used, and that isometry cannot be discarded in both cases. However, if the effects of body mass are removed, a null slope cannot be discarded. On the other hand, when body mass (BM) is taken as the independent variable and PCOA as the dependent one, the slope obtained evidences a negative allometry, and this holds also when phylogenetic control is used. Given these contradictory results, we suggest that the rule of 'equivalence between exponents' is not a good approach for obtaining inferences on the function of postcanine teeth. The argument for the existence or absence of a given relationship between two variables is based on the p value used for testing the null hypothesis H0 (ß1=0), which is independent of the value taken by the slope of one of these variables when regressed on a third one. In any case, BM emerges as a key factor in the relationship between PCOA and BRM. |
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