There is increasing concern about the decline of pollinators worldwide. However, despite reports that pollinator declines are widespread, data are scarce and often geographically and taxonomically biased. These biases limit robust inference about any potential pollinator crisis. Non-structured and opportunistic historical specimen collection data provide the only source of historical information which can serve as a baseline for identifying pollinator declines. Specimens historically collected and preserved in museums not only provide information on where and when species were collected, but also contain other ecological information such as species interactions and morphological traits. Here, we provide a synthesis of how researchers have used historical data to identify long-term changes in biodiversity, species abundances, morphology and pollination services. Despite recent advances, we show that information on the status and trends of most pollinators is absent. We highlight opportunities and limitations to progress the assessment of pollinator declines globally. Finally, we demonstrate different approaches to analysing museum collection data using two contrasting case studies from distinct geographical regions (New Zealand and Spain) for which long-term pollinator declines have never been assessed. There is immense potential for museum specimens to play a central role in assessing the extent of the global pollination crisis. This article is part of the theme issue ‘Biological collections for understanding biodiversity in the Anthropocene’.
Historical collections as a tool for assessing the global pollination crisis
I. Bartomeus,J. Stavert,Darren F. Ward,Darren F. Ward,O. Aguado
Published 2018 in Philosophical Transactions of the Royal Society of London. Biological Sciences
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- Publication year
2018
- Venue
Philosophical Transactions of the Royal Society of London. Biological Sciences
- Publication date
2018-11-19
- Fields of study
Biology, Geography, Medicine, Environmental Science
- Identifiers
- External record
- Source metadata
Semantic Scholar, PubMed
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