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• W1983174126 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." @default.
• W1983174126 created "2016-06-24" @default.
• W1983174126 creator A5005854883 @default.
• W1983174126 date "2014-03-01" @default.
• W1983174126 modified "2023-09-27" @default.
• W1983174126 title "Ecological Modeling of Metabolic Rates Predicts Diverging Optima across Food Abundances" @default.
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• W1983174126 doi "https://doi.org/10.1086/674951" @default.
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