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Article
License: CC BY NC ND
Data sources: UnpayWall
https://doi.org/10.1101/457762...
Article . 2018 . Peer-reviewed
Data sources: Crossref
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Biological adaptation under fluctuating selection

Authors: Liu, Ming; Rubenstein, Dustin R.; Liu, Wei-Chung; Shen, Sheng-Feng;

Biological adaptation under fluctuating selection

Abstract

Abstract Bet-hedging—an evolutionary strategy that reduces fitness variance at the expense of lower mean fitness—is the primary explanation for most forms of biological adaptation to environmental unpredictability. However, most applications of bet-hedging theory to biological problems have largely made unrealistic demographic assumptions, such as non-overlapping generations and fixed population sizes. Consequently, the generality and applicability of bet-hedging theory to real world phenomena remains unclear. Here we use continuous-time, stochastic Lotka-Volterra models to relax overly restrictive demographic assumptions and explore a suite of biological adaptations to fluctuating environments. We discover a novel “rising-tide strategy” that—unlike the bet-hedging strategy—generates both a higher mean and variance in fitness. The positive fitness effects of the rising-tide strategy’s specialization to good years can overcome any negative effects of higher fitness variance in unpredictable environments. Moreover, we show not only that the rising-tide strategy will be selected for over a much broader range of environmental conditions than the bet-hedging strategy, but also under more realistic demographic circumstances. Ultimately, our model demonstrates that there are likely to be a wide range of ways that organisms respond to environmental unpredictability.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green