Publications

@article{Marcer2022b,
title = {Uncertainty matters: ascertaining where specimens in natural history collections come from and its implications for predicting species distributions},
author = {Arnald Marcer,Arthur D. Chapman,John R. Wieczorek,F. Xavier Picó,Francesc Uribe,John Waller,Arturo H. Ariño},
url = {https://onlinelibrary.wiley.com/doi/epdf/10.1111/ecog.06025},
doi = {/10.1111/ecog.06025},
issn = {0906-7590, 1600-0587},
year = {2022},
date = {2022-05-09},
journal = {ECOGRAPHY},
volume = {2022},
abstract = {Natural history collections (NHCs) represent an enormous and largely untapped wealth of information on the Earth’s biota, made available through GBIF as digital preserved specimen records. Precise knowledge of where the specimens were collected is paramount to rigorous ecological studies, especially in the field of species distribution modelling. Here, we present a first comprehensive analysis of georeferencing quality for all preserved specimen records served by GBIF, and illustrate the impact that coordinate uncertainty may have on predicted potential distributions. We used all GBIF preserved specimen records to analyse the availability of coordinates and associated spatial uncertainty across geography, spatial resolution, taxonomy, publishing institutions and collection time. We used three plant species across their native ranges in different parts of the world to show the impact of uncertainty on predicted potential distributions. We found that 38% of the 180+ million records provide coordinates only and 18% coordinates and uncertainty. Georeferencing quality is determined more by country of collection and publishing than by taxonomic group. Distinct georeferencing practices are more determinant than implicit characteristics and georeferencing difficulty of specimens. Availability and quality of records contrasts across world regions. Uncertainty values are not normally distributed but peak at very distinct values, which can be traced back to specific regions of the world. Uncertainty leads to a wide spectrum of range sizes when modelling species distributions, potentially affecting conclusions in biogeographical and climate change studies. In summary, the digitised fraction of the world’s NHCs are far from optimal in terms of georeferencing and quality mainly depends on where the collections are hosted. A collective effort between communities around NHC institutions, ecological research and data infrastructure is needed to bring the data on a par with its importance and relevance for ecological research.},
keywords = {ecological niche modelling (ENM), ecological research, GBIF, georeferencing, natural history collections, preserved specimens, species distribution modelling (SDM), Uncertainty},
pubstate = {published},
tppubtype = {article}
}

@article{Marcer2022,
title = {Ali-Bey - an open collaborative georeferencing web application},
author = {Arnald Marcer, Agustí Escobar, Víctor Garcia-Font, Francesc Uribe},
doi = {https://doi.org/10.3897/BDJ.10.e81282},
year = {2022},
date = {2022-04-28},
keywords = {collaborative database, digital specimens, georeferencing, natural history collections, site name versioning, traceability, web application},
pubstate = {published},
tppubtype = {article}
}

@article{Marcer2021,
title = {Natural History Collections Georeferencing Survey Report. Current georeferencing practices across institutions worldwide.},
author = { Marcer, Arnald; Groom, Quentin; Haston, Elspeth; Uribe, Francesc},
doi = {https://doi.org/10.5281/zenodo.4644529},
year = {2021},
date = {2021-03-30},
keywords = {Botanical Garden, Data quality, georeferencing, Herbaria, Natural History Collections (NHC), Natural History Institutions Museum, Uncertainty},
pubstate = {published},
tppubtype = {article}
}

@article{Marcer2020,
title = {Quality issues in georeferencing: From physical collections to digital data repositories for ecological research},
author = {Arnald Marcer,Elspeth Haston,Quentin Groom,Arturo H. Ariño,Arthur D. Chapman,Torkild Bakken,Paul Braun,Mathias Dillen,Marcus Ernst,Agustí Escobar,David Fichtmüller,Laurence Livermore,Nicky Nicolson,Kaloust Paragamian,Deborah Paul,Lars B. Pettersson,Sarah Phillips,Jack Plummer,Heimo Rainer,Isabel Rey,Tim Robertson,Dominik Röpert,Joaquim Santos,Francesc Uribe,John Waller,John R. Wieczorek},
doi = {https://doi.org/10.1111/ddi.13208},
year = {2020},
date = {2020-12-03},
keywords = {eco-evolutionary research, georeferencing, global biodiversity information facility, natural history collections, uncertainty workshop},
pubstate = {published},
tppubtype = {article}
}

@article{10.3897/phytokeys.74.9723,
title = {RAINBIO: a mega-database of tropical African vascular plants distributions},
author = {Gilles Dauby and Rainer Zaiss and Anne Blach-Overgaard and Luís Catarino and Theo Damen and Vincent Deblauwe and Steven Dessein and John Dransfield and Vincent Droissart and Maria Cristina Duarte and Henry Engledow and Geoffrey Fadeur and Rui Figueira and Roy E Gereau and Olivier J Hardy and David J Harris and Janneke de Heij and Steven Janssens and Yannick Klomberg and Alexandra C Ley and Barbara A MacKinder and Pierre Meerts and Jeike L van de Poel and Bonaventure Sonké and Marc S M Sosef and Tariq Stévart and Piet Stoffelen and Jens-Christian Svenning and Pierre Sepulchre and Xander van der Burgt and Jan J Wieringa and Thomas L P Couvreur},
url = {https://doi.org/10.3897/phytokeys.74.9723},
doi = {10.3897/phytokeys.74.9723},
issn = {1314-2011},
year = {2016},
date = {2016-01-01},
journal = {PhytoKeys},
volume = {74},
pages = {1-18},
publisher = {Pensoft Publishers},
abstract = {The tropical vegetation of Africa is characterized by high levels of species diversity but is undergoing important shifts in response to ongoing climate change and increasing anthropogenic pressures. Although our knowledge of plant species distribution patterns in the African tropics has been improving over the years, it remains limited. Here we present RAINBIO, a unique comprehensive mega-database of georeferenced records for vascular plants in continental tropical Africa. The geographic focus of the database is the region south of the Sahel and north of Southern Africa, and the majority of data originate from tropical forest regions. RAINBIO is a compilation of 13 datasets either publicly available or personal ones. Numerous in depth data quality checks, automatic and manual via several African flora experts, were undertaken for georeferencing, standardization of taxonomic names and identification and merging of duplicated records. The resulting RAINBIO data allows exploration and extraction of distribution data for 25,356 native tropical African vascular plant species, which represents ca. 89% of all known plant species in the area of interest. Habit information is also provided for 91% of these species.},
keywords = {biodiversity assessment, cultivated species, digitization, georeferencing, habit, Herbarium specimens, native species, taxonomic backbone, tropical forests},
pubstate = {published},
tppubtype = {article}
}