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Population‐level consequences of polymorphism, plasticity and randomized phenotype switching: a review of predictions
Author(s) -
Wennersten Lena,
Forsman Anders
Publication year - 2012
Publication title -
biological reviews
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 4.993
H-Index - 165
eISSN - 1469-185X
pISSN - 1464-7931
DOI - 10.1111/j.1469-185x.2012.00231.x
Subject(s) - phenotypic plasticity , biology , population , evolutionary biology , natural selection , ecology , variation (astronomy) , phenotype , genetic variation , biodiversity , genetics , demography , physics , sociology , astrophysics , gene
The consequences of among‐individual phenotypic variation for the performance and ecological success of populations and species has attracted growing interest in recent years. Earlier reviews of this field typically address the consequences for population processes of one specific source of variation (plasticity or polymorphism), or consider one specific aspect of population performance, such as rate of speciation. Here we take a broader approach and study earlier reviews in order to summarize and compare predictions regarding several population‐level consequences of phenotypic variation stemming from genetic polymorphism, developmental plasticity or randomized phenotype switching. Unravelling cause‐dependent consequences of variation may increase our ability to understand the ecological dynamics of natural populations and communities, develop more informed management plans for protection of biodiversity, suggest possible routes to increased productivity and yield in natural and managed biological systems, and resolve inconsistencies in patterns and results seen in studies of different model systems. We find an overall agreement regarding the effects of higher levels of phenotypic variation generated by different sources, but also some differences between fine‐grained and coarse‐grained environments, modular and unitary organisms, mobile and sessile organisms, and between flexible and fixed traits. We propose ways to test the predictions and identify issues where current knowledge is limited and future lines of investigation promise to provide important novel insights.

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