Thermal energetics of the New-Guinean moss-forest rat (Rattus niobe) in comparison with other tropical murid rodents

Assigning metabolic rate measurements to torpor and euthermy in heterothermic endotherms: "torpor", a new package for R

Torpor is a state of controlled reduction of metabolic rate (M) in endotherms. Assigning measurements of M to torpor or euthermy can be challenging, especially when the difference between euthermic M and torpid M is small, in species defending a high minimal body temperature in torpor, in thermolabile species, and slightly below the thermoneutral zone (TNZ). Here, we propose a novel method for distinguishing torpor from euthermy. We use the variation in M measured during euthermic rest and torpor at varying ambient temperatures (T_a) to objectively estimate the lower critical temperature (T_lc) of the TNZ and to assign measurements to torpor, euthermic rest or rest within TNZ. In addition, this method allows the prediction of M during euthermic rest and torpor at varying T_a, including resting M within the TNZ. The present method has shown highly satisfactory results using 28 published sets of metabolic data obtained by respirometry on 26 species of mammals. Ultimately, this novel method aims to facilitate analysis of respirometry data in heterothermic endotherms. Finally, the development of the associated R-package (torpor) will enable widespread use of the method amongst biologists.

Summary: The presented method and its associated R-package (torpor) enable the assignment of metabolic rate measurements to torpor or euthermy, ultimately improving the standardization of respirometry analyses in heterotherms.

Comparative analyses of basal rate of metabolism in mammals: data selection does matter

Basal rate of metabolism (BMR) is a physiological parameter that should be measured under strictly defined experimental conditions. In comparative analyses among mammals BMR is widely used as an index of the intensity of the metabolic machinery or as a proxy for energy expenditure. Many databases with BMR values for mammals are available, but the criteria used to select metabolic data as BMR estimates have often varied and the potential effect of this variability has rarely been questioned. We provide a new, expanded BMR database reflecting compliance with standard criteria (resting, postabsorptive state; thermal neutrality; adult, non-reproductive status for females) and examine potential effects of differential selectivity on the results of comparative analyses. The database includes 1739 different entries for 817 species of mammals, compiled from the original sources. It provides information permitting assessment of the validity of each estimate and presents the value closest to a proper BMR for each entry. Using different selection criteria, several alternative data sets were extracted and used in comparative analyses of (i) the scaling of BMR to body mass and (ii) the relationship between brain mass and BMR. It was expected that results would be especially dependent on selection criteria with small sample sizes and with relatively weak relationships. Phylogenetically informed regression (phylogenetic generalized least squares, PGLS) was applied to the alternative data sets for several different clades (Mammalia, Eutheria, Metatheria, or individual orders). For Mammalia, a 'subsampling procedure' was also applied, in which random subsamples of different sample sizes were taken from each original data set and successively analysed. In each case, two data sets with identical sample size and species, but comprising BMR data with different degrees of reliability, were compared. Selection criteria had minor effects on scaling equations computed for large clades (Mammalia, Eutheria, Metatheria), although less-reliable estimates of BMR were generally about 12-20% larger than more-reliable ones. Larger effects were found with more-limited clades, such as sciuromorph rodents. For the relationship between BMR and brain mass the results of comparative analyses were found to depend strongly on the data set used, especially with more-limited, order-level clades. In fact, with small sample sizes (e.g. <100) results often appeared erratic. Subsampling revealed that sample size has a non-linear effect on the probability of a zero slope for a given relationship. Depending on the species included, results could differ dramatically, especially with small sample sizes. Overall, our findings indicate a need for due diligence when selecting BMR estimates and caution regarding results (even if seemingly significant) with small sample sizes.