Quantitative Biology

Sexual Complexity as a Screen for Replication Fidelity: the Everest Effect

Authors: Patrick D Shaw Stewart
Comments: 31 Pages.

Sexual reproduction is widespread among complex organisms, yet its elaborate accompaniments—from courtship displays to molecular recognition systems—remain incompletely explained. The Everest hypothesis rests on four propositions: (1) environmental change can shift the drift-barrier equilibrium toward higher mutation rates, as beneficial mutations become more common and mutator alleles hitchhike during adaptation; (2) many lineages reproduce through systems whose elaboration exceeds what fertilization or viability-fecundity benefits can explain; (3) such elaboration enlarges the mutational target by involving additional coding or regulatory DNA; and (4) mutations affecting those loci often reduce mating or fertilization success. If these propositions are broadly correct, reproductive complexity should couple replication fidelity to reproductive success. This coupling is the Everest effect: complex reproductive systems expose even mild mutators—whose effects may be too weak for ordinary viability-fecundity selection to purge reliably—to appreciable reproductive penalties. The hypothesis casts sexual selection as both accelerator and brake: during environmental change, mate choice can accelerate adaptation by favoring high-performing individuals, often arising from mutator backgrounds. After conditions stabilize, demanding reproductive screens can expose accumulated damage from elevated mutation rates, allowing mate choice or fertilization success to purge mutator lineages. Recombination then allows adaptive alleles to be retained while high fidelity is restored. Everest complements Fisherian, handicap, and good-genes processes by proposing that traits elaborated by those processes can also be co-opted as fidelity-linked reproductive screens. An individual-based simulation and proposed experimental, comparative, and genomic tests show how the hypothesis can be evaluated.
Category: Quantitative Biology