Moths complement bumblebee pollination of red clover: a case for day-and-night insect surveillance

Alison, Jamie ORCID: https://orcid.org/0000-0002-6787-6192; Alexander, Jake M.; Diaz Zeugin, Nathan; Dupont, Yoko L.; Iseli, Evelin; Mann, Hjalte M.R.; Høye, Toke T.. 2022 Moths complement bumblebee pollination of red clover: a case for day-and-night insect surveillance. Biology Letters, 18 (7), 20220187. 5, pp. 10.1098/rsbl.2022.0187

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Abstract/Summary

Recent decades have seen a surge in awareness about insect pollinator declines. Social bees receive the most attention, but most flower-visiting species are lesser known, non-bee insects. Nocturnal flower visitors, e.g. moths, are especially difficult to observe and largely ignored in pollination studies. Clearly, achieving balanced monitoring of all pollinator taxa represents a major scientific challenge. Here, we use time-lapse cameras for season-wide, day-and-night pollinator surveillance of Trifolium pratense (L.; red clover) in an alpine grassland. We reveal the first evidence to suggest that moths, mainly Noctua pronuba (L.; large yellow underwing), pollinate this important wildflower and forage crop, providing 34% of visits (bumblebees: 61%). This is a remarkable finding; moths have received no recognition throughout a century of T. pratense pollinator research. We conclude that despite a non-negligible frequency and duration of nocturnal flower visits, nocturnal pollinators of T. pratense have been systematically overlooked. We further show how the relationship between visitation and seed set may only become clear after accounting for moth visits. As such, population trends in moths, as well as bees, could profoundly affect T. pratense seed yield. Ultimately, camera surveillance gives fair representation to non-bee pollinators and lays a foundation for automated monitoring of species interactions in future.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	10.1098/rsbl.2022.0187
UKCEH and CEH Sections/Science Areas:	Soils and Land Use (Science Area 2017-)
ISSN:	1744-957X
Additional Information. Not used in RCUK Gateway to Research.:	Open Access paper - full text available via Official URL link.
Additional Keywords:	entomology, computer vision, biodiversity, phenology, conservation, Lepidoptera
NORA Subject Terms:	Ecology and Environment
Date made live:	30 Dec 2022 18:35 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/533781

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