According to accepted evolutionary theories, aging has evolved as a side-effect of strong selection pressure for early fertility, despite the fact that it has no adaptive value of its own. I have argued elsewhere that recent experimental results make these theories untenable, and that there is now a broad array of evidence indicating that aging has evolved as an adaptation, selected for its own sake. To explain nature's preference for aging is a substantial theoretical challenge. The classical Weismann hypothesis, "making room for the young," fails because the benefit to the population accrues in the form of enhancement to the rate of increase of population average fitness, while the cost affects individual fitness directly and efficiently. In multi-level selection models, the aging genes are lost before their benefit can accumulate. I propose here that aging has evolved based on a different benefit: its contribution to demographic homeostasis. I argue that population dynamics are inherently chaotic, and that the stable ecosystems that we commonly observe in nature are a highly evolved phenomenon. Natural selection for population homeostasis is far more efficient than selection for rate of evolution because chaotic population dynamics can be lethal on a time scale of just a few generations, while enhanced rate of evolution takes far longer to affect population mean fitness. My thesis is that aging can evolve based on its ability to damp population fluctuations. For illustration, I offer an individual-based computational model that reproduces chaotic population dynamics with a delayed-feedback logistic equation. Genes for aging emerge handily.
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