Effects of extrinsic mortality on the evolution of aging: a stochastic modeling approach.
The evolutionary theories of aging are useful for gaining insights into the complex mechanisms underlying senescence. Classical theories argue that high levels of extrinsic mortality should select for the evolution of shorter lifespans and earlier peak fertility. Non-classical theories, in contrast, posit that an increase in extrinsic mortality could select for the evolution of longer lifespans. Although numerous studies support the classical paradigm, recent data challenge classical predictions, finding that high extrinsic mortality can select for the evolution of longer lifespans. To further elucidate the role of extrinsic mortality in the evolution of aging, we implemented a stochastic, agent-based, computational model. We used a simulated annealing optimization approach to predict which model parameters predispose populations to evolve longer or shorter lifespans in response to increased levels of predation. We report that longer lifespans evolved in the presence of rising predation if the cost of mating is relatively high and if energy is available in excess. Conversely, we found that dramatically shorter lifespans evolved when mating costs were relatively low and food was relatively scarce. We also analyzed the effects of increased predation on various parameters related to density dependence and energy allocation. Longer and shorter lifespans were accompanied by increased and decreased investments of energy into somatic maintenance, respectively. Similarly, earlier and later maturation ages were accompanied by increased and decreased energetic investments into early fecundity, respectively. Higher predation significantly decreased the total population size, enlarged the shared resource pool, and redistributed energy reserves for mature individuals. These results both corroborate and refine classical predictions, demonstrating a population-level trade-off between longevity and fecundity and identifying conditions that produce both classical and non-classical lifespan effects.
Program in Bioinformatics and Systems Biology, University of California San Diego, La Jolla, California, United States of America.
Maxim Nikolaievich
MN
Shokhirev
Physiological Sciences Graduate Interdisciplinary Program, University of Arizona, Tucson, Arizona, United States of America.
Adiv Adam
AA
Johnson
D000375:Aging / Q000502:physiology*; D005075:Biological Evolution; D003198:Computer Simulation; D004734:Energy Metabolism / Q000502:physiology; D006801:Humans; D008136:Longevity / Q000502:physiology*; D011156:Population Density