4.5.3 Relationship between metabolic performance and body composition 4.5.3.1 BMR
Considering data for the whole year, the best model (F^6i - 16.0 p< 0.0001), explaining 32% of the variation in BMR, included the residual mass of muscles (FI|6I = 27.6, p< 0.0001, P = 0.52) and residual mass of the excretory organs (Fi,6i = 4.5, p < 0.05, p = 0.22). During the fali, variations in BMR were best explained (r2^ = 0.30) by a model (Fi,h= 7.5, p<0.05) including only residual muscle mass (Fi. ł4= 7.5, p<0.05, P = 0.59) while in midwinter, 43% (F3>19= 6.5, p < 0.01) of the variation in BMR was explained by a combination of the residual mass of excretoiy organs (Fj, ]9 = 13.0, p < 0.01, p = 0.60), brain (Fłt ,9= 4.8, p < 0.05, P = 0.43) and the lean dry mass of digestive organs (p = 0.2). Analyses for the end of winter revealed that the best model (Fj, |2 = 8.1, p<0.05, r2^ = 0.35) explaining BMR variations included only residual muscle mass (Fjt 12 = 8.1, p < 0.05, p = 0.63) while during the summer, the best model was the nuli model (figurę 4.5).
4.5.3.2 Msum
Model selection showed that over the whole year, Msum variations were best explained (F3>2=32.9, p< 0.0001, r2*# = 0.64) by a combination of residual lean dry muscle mass (F|.52 = 33.6, p< 0.0001, p = 0.60), residual mass of cardiopulmonary organs (Fił52=62.4, p< 0.0001, P = 31) and residual excretory organ mass (p = 0.1). In the fali, model selection produced a model (Fj.9 = 10.3, p < 0.05, = 0.48) that included the lean dry mass of digestive
organs (Fit 9 = 10.3, p<0.05, p = 0.73) while for midwinter, the best model (Ftł 20 = 28.2, p< 0.0001), explaining 56% of the variation in Msum, included only the residual mass of muscles (Fit20=28.2, p< 0.0001, p = 0.76). Similarly, at the end of winter, the best model (Fij0= 10.3, p< 0.01) explained 46% of Msum variation and included only residual muscle mass (Fj, 10= 10.3, p < 0.01, p = 0.71). Finally, in the summer, no organs were found to explain any significant part of variations in Msum (figurę 4.5).