Pollinator importance networks illustrate the crucial value of bees in a highly speciose plant community

Ballantyne, Gavin; Baldock, Katherine C. R.; Rendell, Luke; Willmer, Pat

Abstract

Accurate predictions of pollination service delivery require a comprehensive understanding of the interactions between plants and flower visitors. To improve measurements of pollinator performance underlying such predictions, we surveyed visitation frequency, pollinator effectiveness (pollen deposition ability) and pollinator importance (the product of visitation frequency and effectiveness) of flower visitors in a diverse Mediterranean flower meadow. With these data we constructed the largest pollinator importance network to date and compared it with the corresponding visitation network to estimate the specialisation of the community with greater precision. Visitation frequencies at the community level were positively correlated with the amount of pollen deposited during individual visits, though rarely correlated at lower taxonomic resolution. Bees had the highest levels of pollinator effectiveness, with Apis, Andrena, Lasioglossum and Osmiini bees being the most effective visitors to a number of plant species. Bomblyiid flies were the most effective non-bee flower visitors. Predictions of community specialisation (H2′) were higher in the pollinator importance network than the visitation network, mirroring previous studies. Our results increase confidence in existing measures of pollinator redundancy at the community level using visitation data, while also providing detailed information on interaction quality at the plant species level.

Citation

Ballantyne, G., Baldock, K. C. R., Rendell, L., & Willmer, P. (2017). Pollinator importance networks illustrate the crucial value of bees in a highly speciose plant community. Scientific Reports, 7(1), Article 8389. https://doi.org/10.1038/s41598-017-08798-x

• Journal Article Type: Article
• Acceptance Date: Jul 17, 2017
• Online Publication Date: Aug 21, 2017
• Publication Date: 2017-12
• Deposit Date: Aug 21, 2017
• Publicly Available Date: Aug 21, 2017
• Journal: Scientific Reports
• Electronic ISSN: 2045-2322
• Publisher: Nature Publishing Group
• Peer Reviewed: Peer Reviewed
• Volume: 7
• Issue: 1
• Article Number: 8389
• DOI: https://doi.org/10.1038/s41598-017-08798-x
• Keywords: Ecological networks, ecosystem ecology,
• Public URL: http://researchrepository.napier.ac.uk/Output/978024