4.5 Article

The reproductive assurance benefit of selfing: importance of flower size and population size

期刊

OECOLOGIA
卷 155, 期 3, 页码 469-477

出版社

SPRINGER
DOI: 10.1007/s00442-007-0924-7

关键词

autonomous selfing; Collinsia parviflora; habitat fragmentation; pollen limitation; reproductive assurance

类别

向作者/读者索取更多资源

Autonomous selfing can provide reproductive assurance (RA) for flowering plants that are unattractive to pollinators or in environments that are pollen limited. Pollen limitation may result from the breakdown of once-continuous habitat into smaller, more isolated patches (habitat fragmentation) if fragmentation negatively impacts pollinator populations. Here we quantify the levels of pollen limitation and RA among large and small populations of Collinsia parviflora, a wildflower with inter-population variation in flower size. We found that none of the populations were pollen limited, as pollen-supplemented and intact flowers did not differ in seed production. There was a significant effect of flower size on RA; intact flowers (can self) produced significantly more seeds than emasculated flowers (require pollen delivery) in small-flowered plants but not large-flowered plants. Population size nested within flower size did not significantly affect RA, but there was a large difference between our two replicate populations for large-flowered, small populations and small-flowered, large populations that appears related to a more variable pollination environment under these conditions. In fact, levels of RA were strongly negatively correlated with rates of pollinator visitation, whereby infrequent visitation by pollinators yielded high levels of RA via autonomous selfing, but there was no benefit of autonomous selfing when visitation rates were high. These results suggest that autonomous selfing may be adaptive in fragmented habitats or other ecological circumstances that affect pollinator visitation rates.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.5
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据