Ecological modeling of metabolic rates predicts diverging optima across food abundances

Abstract

Genetically based variation in metabolic rates of resting animals (RMR) suggests a potential role for evolutionary adaptations, but mechanistic models yielding evolutionary predictions are lacking. Here I utilize the increasingly recognized genetic correlation between RMR and activity metabolism and propose that optimality of the former is simply an outcome of selection on the latter. I develop a model for temporally stable environmental conditions that describes how the rate of acquisition of energy that can be converted into somatic growth and reproductive output can be expressed as a function of activity metabolism. One of the parameters in the model describes how food intake depends on activity and is hence a measure of food abundance. In contrast to the previously proposed hypothesis that individuals with a high RMR are at an advantage when environmental conditions are favorable, the model predicts that the optimal RMR is highest at an intermediate food abundance.