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Consequences of combining sex-specific traits

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Venkateswaran,  Vandana Revathi
IMPRS for Evolutionary Biology, Max Planck Institute for Evolutionary Biology, Max Planck Society;
Research Group Theoretical Models of Eco-Evolutionary Dynamics, Department Evolutionary Theory, Max Planck Institute for Evolutionary Biology, Max Planck Society;

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Gokhale,  Chaitanya S.
Research Group Theoretical Models of Eco-Evolutionary Dynamics, Department Evolutionary Theory, Max Planck Institute for Evolutionary Biology, Max Planck Society;

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引用

Venkateswaran, V. R., Roth, O., & Gokhale, C. S. (2021). Consequences of combining sex-specific traits. Evolution: international journal of organic evolution, 75(6), 1274-1287. doi:10.1111/evo.14204.


引用: https://hdl.handle.net/21.11116/0000-0005-87ED-8
要旨
Males and females follow distinct life-history strategies that have co-evolved with several sex-specific traits. Higher investment intoparental investment (PI) demands an increased lifespan. Thus, resource allocation toward an efficient immune system is mandatory.In contrast, resources allocated toward secondary sexual signals (ornamentation) may negatively correlate with investment intoimmunity and ultimately result in a shorter lifespan. Previous studies have addressed how resource allocation toward single sex-specific traits impacts lifetime reproductive success (LRS). However, the trade-offs between diverse sex-specific characteristics andtheir impact on LRS remain largely unassessed impeding our understanding of life-history evolution. We have designed a theoreticalframework (informed by experimental data and evolutionary genetics) that explores the effects of multiple sex-specific traits andassessed how they influence LRS. From the individual sex-specific traits, we inferred the consequences at the population levelby evaluating adult sex ratios (ASR). Our theory implies that sex-specific resource allocation toward the assessed traits resultedin a biased ASR. Our model focuses on the impact of PI, ornamentation, and immunity as causal to biased ASR. The frameworkdeveloped herein can be employed to understand the combined impact of diverse sex-specific traits on the LRS and the eventualpopulation dynamics of particular model systems.