dc.contributor.author
Marcer, Arnald
dc.contributor.author
Chapman, Arthur D.
dc.contributor.author
Wieczorek, John R.
dc.contributor.author
Picó, Francesc X.
dc.contributor.author
Uribe, Francesc
dc.contributor.author
Waller, John
dc.contributor.author
Ariño, Arturo H.
dc.date.accessioned
2022-06-20T07:26:22Z
dc.date.accessioned
2024-07-29T07:43:11Z
dc.date.available
2022-06-20T07:26:22Z
dc.date.available
2024-07-29T07:43:11Z
dc.identifier.uri
http://hdl.handle.net/2072/522462
dc.description
Data are available from the Zenodo Digital Repository: https://doi.org/10.5281/zenodo.5052596, (derived dataset GBIF.org (6 July 2021)) (Marcer et al. 2022).
dc.description.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.
eng
dc.relation.ispartof
Ecography, e06025 (2022)
dc.rights
L'accés als continguts d'aquest document queda condicionat a l'acceptació de les condicions d'ús establertes per la següent llicència Creative Commons:http://creativecommons.org/licenses/by/4.0/
dc.rights
© 2022 The Authors. Ecography published by John Wiley & Sons Ltd on behalf of Nordic Society Oikos
dc.source
RECERCAT (Dipòsit de la Recerca de Catalunya)
dc.subject.other
Col·leccions de ciències naturals
dc.subject.other
Biogeografia
dc.subject.other
Dades geoespacials
dc.title
Uncertainty matters: ascertaining where specimens in natural history collections come from and its implications for predicting species distributions
dc.type
info:eu-repo/semantics/article
dc.type
info:eu-repo/semantics/publishedVersion
dc.rights.accessLevel
info:eu-repo/semantics/openAccess