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Enhancing georeferenced biodiversity inventories: automated information extraction from literature records reveal the gaps

View ORCID ProfileBjørn Tore Kopperud, Scott Lidgard, View ORCID ProfileLee Hsiang Liow
doi: https://doi.org/10.1101/2020.01.16.908962
Bjørn Tore Kopperud
1Natural History Museum, University of Oslo, PO Box 1172 Blindern, 0318 Oslo, Norway
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Scott Lidgard
2Negaunee Integrative Research Center, Field Museum, 1400 South Lake Shore Drive, Chicago IL, 60605, U.S.A
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Lee Hsiang Liow
1Natural History Museum, University of Oslo, PO Box 1172 Blindern, 0318 Oslo, Norway
3Centre for Ecological and Evolutionary Synthesis, Department of Biosciences, University of Oslo, PO Box 1066 Blindern, 0316 Oslo, Norway
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  • For correspondence: l.h.liow@nhm.uio.no
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Abstract

We use natural language processing (NLP) to retrieve location data for cheilostome bryozoan species (text-mined occurrences [TMO]) in an automated procedure. We compare these results with data from the Ocean Biogeographic Information System (OBIS). Using OBIS and TMO data separately and in combination, we present latitudinal species richness curves using standard estimators (Chao2 and the Jackknife) and range-through approaches. Our combined OBIS and TMO species richness curves quantitatively document a bimodal global latitudinal diversity gradient for cheilostomes for the first time, with peaks in the temperate zones. 79% of the georeferenced species we retrieved from TMO (N = 1780) and OBIS (N = 2453) are non-overlapping and underestimate known species richness, even in combination. Despite clear indications that global location data compiled for cheilostomes should be improved with concerted effort, our study supports the view that latitudinal species richness patterns deviate from the canonical LDG. Moreover, combining online biodiversity databases with automated information retrieval from the published literature is a promising avenue for expanding taxon-location datasets.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted January 17, 2020.
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Enhancing georeferenced biodiversity inventories: automated information extraction from literature records reveal the gaps
Bjørn Tore Kopperud, Scott Lidgard, Lee Hsiang Liow
bioRxiv 2020.01.16.908962; doi: https://doi.org/10.1101/2020.01.16.908962
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Enhancing georeferenced biodiversity inventories: automated information extraction from literature records reveal the gaps
Bjørn Tore Kopperud, Scott Lidgard, Lee Hsiang Liow
bioRxiv 2020.01.16.908962; doi: https://doi.org/10.1101/2020.01.16.908962

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