Andrew, Carrie, Heegaard, Einar, Kirk, Paul M., Bässler, Claus, Heilmann-Clausen, Jacob, Krisai-Greilhuber, Irmgard, Kuyper, Thomas W., Senn-Irlet, Beatrice, Büntgen, Ulf, Diez, Jeffrey, Egli, Simon, Gange, Alan C., Halvorsen, Rune, Høiland, Klaus, Nordén, Jenni, Rustøen, Fredrik, Boddy, Lynne ORCID: https://orcid.org/0000-0003-1845-6738 and Kauserud, Håvard 2017. Big data integration: Pan-European fungal species observations' assembly for addressing contemporary questions in ecology and global change biology. Fungal Biology Reviews 31 (2) , pp. 88-98. 10.1016/j.fbr.2017.01.001 |
Abstract
Species occurrence observations are increasingly available for scientific analyses through citizen science projects and digitization of museum records, representing a largely untapped ecological resource. When combined with open-source data, there is unparalleled potential for understanding many aspects of the ecology and biogeography of organisms. Here we describe the process of assembling a pan-European mycological meta-database (ClimFun) and integrating it with open-source data to advance the fields of macroecology and biogeography against a backdrop of global change. Initially 7.3 million unique fungal species fruit body records, spanning nine countries, were processed and assembled into 6 million records of more than 10,000 species. This is an extraordinary amount of fungal data to address macro-ecological questions. We provide two examples of fungal species with different life histories, one ectomycorrhizal and one wood decaying, to demonstrate how such continental-scale meta-databases can offer unique insights into climate change effects on fungal phenology and fruiting patterns in recent decades.
Item Type: | Article |
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Date Type: | Publication |
Status: | Published |
Schools: | Biosciences |
Subjects: | G Geography. Anthropology. Recreation > GF Human ecology. Anthropogeography Q Science > QH Natural history > QH301 Biology |
Uncontrolled Keywords: | Biogeography; Citizen science; Fungi; Global change; Meta-database; Open-source |
Publisher: | Elsevier |
ISSN: | 1749-4613 |
Date of Acceptance: | 5 January 2017 |
Last Modified: | 21 Oct 2022 07:16 |
URI: | https://orca.cardiff.ac.uk/id/eprint/99513 |
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