Cooperative interactions among females can lead to even more extraordinary sex ratios. Issue 4 (1st August 2021)

• Record Type: Journal Article
• Authors: Iritani, Ryosuke; West, Stuart A.; Abe, Jun
• Is Part Of: Evolution letters. Volume 5:Issue 4(2021)
• Page Start: 370
• Page End: 384
• Publication Date: 2021-08-01
• Subjects: Cooperation -- Kin selection -- Local resource competition -- Local mate competition -- Local resource enhancement -- Sex-biased dispersal; Evolution (Biology) -- Periodicals; Evolution (Biology); Biological Evolution; Electronic journals; Fulltext; Internet Resources; Periodicals; Periodicals; Periodical; 576.8
• DOI: 10.1002/evl3.217
• Languages: English
• ISSNs: 2056-3744

Abstract

Abstract: Hamilton's local mate competition theory provided an explanation for extraordinary female-biased sex ratios in a range of organisms. When mating takes place locally, in structured populations, a female-biased sex ratio is favored to reduce competition between related males, and to provide more mates for males. However, there are a number of wasp species in which the sex ratios appear to more female biased than predicted by Hamilton's theory. It has been hypothesized that the additional female bias in these wasp species results from cooperative interactions between females. We investigated theoretically the extent to which cooperation between related females can interact with local mate competition to favor even more female-biased sex ratios. We found that (i) cooperation between females can lead to sex ratios that are more female biased than predicted by local competition theory alone, and (ii) sex ratios can be more female biased when the cooperation occurs from offspring to mothers before dispersal, rather than cooperation between siblings after dispersal. Our models formally confirm the verbal predictions made in previous experimental studies, which could be applied to a range of organisms. Specifically, cooperation can help explain sex ratio biases in Sclerodermus and Melittobia wasps, although quantitative comparisons between predictions and data suggest that some additional factors may be operating.