Diffusion plays a prominent role in governing both rates of aerobic metabolic fluxes and mitochondrial organization in muscle fibers. However, there is no mechanism to explain how the non-homogeneous mitochondrial distributions that are prevalent in skeletal muscle arise. We propose that spatially variable degradation with dependence on O(2) concentration, and spatially uniform signals for biogenesis, can account for observed distributions of mitochondria in a diversity of skeletal muscle. We used light and transmission electron microscopy and stereology to examine fiber size, capillarity and mitochondrial distribution in fish red and white muscle, fish white muscle that undergoes extreme hypertrophic growth, and four fiber types in mouse muscle. The observed distributions were compared with those generated using a coupled reaction-diffusion/cellular automata (CA) mathematical model of mitochondrial function. Reaction-diffusion analysis of metabolites such as oxygen, ATP, ADP and PCr involved in energy metabolism and mitochondrial function were considered. Coupled to the reaction-diffusion approach was a CA approach governing mitochondrial life cycles in response to the metabolic state of the fiber. The model results were consistent with the experimental observations and showed higher mitochondrial densities near the capillaries because of the sometimes steep gradients in oxygen. The present study found that selective removal of mitochondria in the presence of low prevailing local oxygen concentrations is likely the primary factor dictating the spatial heterogeneity of mitochondria in a diversity of fibers. The model results also suggest decreased diffusional constraints corresponding to the heterogeneous mitochondrial distribution assessed using the effectiveness factor, defined as the ratio of the reaction rate in the system with finite rates of diffusion to that in the absence of any diffusion limitation. Thus, the non-uniform distribution benefits the muscle fiber by increasing the energy status and increasing sustainable metabolic rates.