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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Trends in Ecology & ...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Trends in Ecology & Evolution
Article . 2016 . Peer-reviewed
License: Elsevier TDM
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Multilevel Selection in Kin Selection Language

Authors: Jussi, Lehtonen;

Multilevel Selection in Kin Selection Language

Abstract

Few issues have raised more debate among evolutionary biologists than kin selection (KS) versus multilevel selection (MLS). They are formally equivalent, but use different-looking mathematical approaches, and are not causally equivalent: for a given problem KS can be a more suitable causal explanation than MLS, and vice versa. Methods for analyzing a given model from both viewpoints would therefore be valuable. I argue that there is often an easy way to achieve this: MLS can be written using the components of KS. This applies to the very general regression approach as well as to the practical evolutionarily stable strategy (ESS) maximization approach, and can hence be used to analyze many common ESS models from a multilevel perspective. I demonstrate this with example models of gamete competition and limitation.

Related Organizations
Keywords

Animals, Selection, Genetic, Social Behavior, Biological Evolution

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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!
25
Top 10%
Average
Top 10%
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