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Evolution in alternating environments with tunable interlandscape correlations

delete2020-12-13
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OA
AI
J
Jeff Maltas
D
Douglas M. McNally
K
Kevin B. Wood *
DOI:10.1111/evo.14121delete
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Abstract

Abstract

En 中文
Natural populations are often exposed to temporally varying environments. Evolutionary dynamics in varying environments have been extensively studied, although understanding the effects of varying selection pressures remains challenging. Here, we investigate how cycling between a pair of statistically related fitness landscapes affects the evolved fitness of an asexually reproducing population. We construct pairs of fitness landscapes that share global fitness features but are correlated with one another in a tunable way, resulting in landscape pairs with specific correlations. We find that switching between these landscape pairs, depending on the ruggedness of the landscape and the interlandscape correlation, can either increase or decrease steady-state fitness relative to evolution in single environments. In addition, we show that switching between rugged landscapes often selects for increased fitness in both landscapes, even in situations where the landscapes themselves are anticorrelated. We demonstrate that positively correlated landscapes often possess a shared maximum in both landscapes that allows the population to step through sub-optimal local fitness maxima that often trap single landscape evolution trajectories. Finally, we demonstrate that switching between anticorrelated paired landscapes leads to ergodic-like dynamics where each genotype is populated with nonzero probability, dramatically lowering the steady-state fitness in comparison to single landscape evolution.
Keywords:
Adaptation
Epistasis
Fitness
Models
Simulations
Population Genetics
Selection‐ Natural
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E
Evolution
IF:
2.6
Papers:
6.5K
Citations:
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U
University of Michigan
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Citations: 124
U
university of michigan system
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Citations: 133