Back to Search Start Over

Body size as a latent variable in a structural equation model: thermal acclimation and energetics of the leaf-eared mouse

Authors :
Roberto F. Nespolo
Matías Arim
Francisco Bozinovic
Source :
Journal of Experimental Biology. 206:2145-2157
Publication Year :
2003
Publisher :
The Company of Biologists, 2003.

Abstract

SUMMARYBody size is one of the most important determinants of energy metabolism in mammals. However, the usual physiological variables measured to characterize energy metabolism and heat dissipation in endotherms are strongly affected by thermal acclimation, and are also correlated among themselves. In addition to choosing the appropriate measurement of body size, these problems create additional complications when analyzing the relationships among physiological variables such as basal metabolism, non-shivering thermogenesis,thermoregulatory maximum metabolic rate and minimum thermal conductance, body size dependence, and the effect of thermal acclimation on them.We measured these variables in Phyllotis darwini, a murid rodent from central Chile, under conditions of warm and cold acclimation. In addition to standard statistical analyses to determine the effect of thermal acclimation on each variable and the body-mass-controlled correlation among them, we performed a Structural Equation Modeling analysis to evaluate the effects of three different measurements of body size (body mass, mb; body length, Lb and foot length, Lf) on energy metabolism and thermal conductance. We found that thermal acclimation changed the correlation among physiological variables. Only cold-acclimated animals supported our a priori path models, and mb appeared to be the best descriptor of body size (compared with Lb and Lf) when dealing with energy metabolism and thermal conductance. However, while mb appeared to be the strongest determinant of energy metabolism, there was an important and significant contribution of Lb (but not Lf) to thermal conductance. This study demonstrates how additional information can be drawn from physiological ecology and general organismal studies by applying Structural Equation Modeling when multiple variables are measured in the same individuals.

Details

ISSN :
14779145 and 00220949
Volume :
206
Database :
OpenAIRE
Journal :
Journal of Experimental Biology
Accession number :
edsair.doi.dedup.....31bdbc31c07a6c3c73bbd33a4150f724