five

Data from: Sex-specific effects of inbreeding on reproductive senescence

收藏
DataCite Commons2025-06-01 更新2025-04-10 收录
下载链接:
https://datadryad.org/dataset/doi:10.5061/dryad.4nr40
下载链接
链接失效反馈
官方服务:
资源简介:
Inbreeding depression plays a significant role in evolutionary biology and ecology. Yet, we lack a clear understanding of the fitness consequences of inbreeding depression. Studies often focus on short-term effects of inbreeding in juvenile offspring whereas inbreeding depression in adult traits and the interplay between inbreeding depression and age is rarely addressed. Inbreeding depression may increase with age and accelerate the decline in reproductive output in ageing individuals (‘reproductive senescence’), which could be subject to sex-specific dynamics. We test this hypothesis with a longitudinal experimental study in a short-lived songbird. Adult inbred and outbred male and female canaries were paired in a 2x2 factorial design and survival and annual reproductive performance were studied for three years. We found inbreeding depression in female egg-laying ability, male fertilization success and survival of both sexes. Annual reproductive success of both males and females declined when paired with an inbred partner independent of their own inbreeding status. This shows that inbreeding can have fitness costs in outbred individuals when they mate with an inbred individual. Further, inbred females showed faster reproductive senescence than outbred females, confirming that inbreeding depression and age can interact to affect fitness. In contrast, there was no evidence for an interaction between inbreeding depression and reproductive senescence in male fertilization success. Our findings highlight the importance of considering sex-specific effects and age to determine the full range of fitness consequences of inbreeding and demonstrate that inbreeding depression can accelerate reproductive senescence.
提供机构:
Dryad
创建时间:
2018-04-25
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作