Estimating species diversity and distribution in the era of Big Data: to what extent can we trust public databases?. Issue 8 (25th May 2015)
- Record Type:
- Journal Article
- Title:
- Estimating species diversity and distribution in the era of Big Data: to what extent can we trust public databases?. Issue 8 (25th May 2015)
- Main Title:
- Estimating species diversity and distribution in the era of Big Data: to what extent can we trust public databases?
- Authors:
- Maldonado, Carla
Molina, Carlos I.
Zizka, Alexander
Persson, Claes
Taylor, Charlotte M.
Albán, Joaquina
Chilquillo, Eder
Rønsted, Nina
Antonelli, Alexandre - Abstract:
- <abstract abstract-type="main"> <title>Abstract</title> <sec id="geb12326-sec-0001" sec-type="section"> <title>Aim</title> <p>Massive digitalization of natural history collections is now leading to a steep accumulation of publicly available species distribution data. However, taxonomic errors and geographical uncertainty of species occurrence records are now acknowledged by the scientific community – putting into question to what extent such data can be used to unveil correct patterns of biodiversity and distribution. We explore this question through quantitative and qualitative analyses of uncleaned versus manually verified datasets of species distribution records across different spatial scales.</p> </sec> <sec id="geb12326-sec-0002" sec-type="section"> <title>Location</title> <p>The American tropics.</p> </sec> <sec id="geb12326-sec-0003" sec-type="section"> <title>Methods</title> <p>As test case we used the plant tribe Cinchoneae (Rubiaceae). We compiled four datasets of species occurrences: one created manually and verified through classical taxonomic work, and the rest derived from GBIF under different cleaning and filling schemes. We used new bioinformatic tools to code species into grids, ecoregions, and biomes following WWF's classification. We analysed species richness and altitudinal ranges of the species.</p> </sec> <sec id="geb12326-sec-0004" sec-type="section"> <title>Results</title> <p>Altitudinal ranges for species and genera were correctly inferred even<abstract abstract-type="main"> <title>Abstract</title> <sec id="geb12326-sec-0001" sec-type="section"> <title>Aim</title> <p>Massive digitalization of natural history collections is now leading to a steep accumulation of publicly available species distribution data. However, taxonomic errors and geographical uncertainty of species occurrence records are now acknowledged by the scientific community – putting into question to what extent such data can be used to unveil correct patterns of biodiversity and distribution. We explore this question through quantitative and qualitative analyses of uncleaned versus manually verified datasets of species distribution records across different spatial scales.</p> </sec> <sec id="geb12326-sec-0002" sec-type="section"> <title>Location</title> <p>The American tropics.</p> </sec> <sec id="geb12326-sec-0003" sec-type="section"> <title>Methods</title> <p>As test case we used the plant tribe Cinchoneae (Rubiaceae). We compiled four datasets of species occurrences: one created manually and verified through classical taxonomic work, and the rest derived from GBIF under different cleaning and filling schemes. We used new bioinformatic tools to code species into grids, ecoregions, and biomes following WWF's classification. We analysed species richness and altitudinal ranges of the species.</p> </sec> <sec id="geb12326-sec-0004" sec-type="section"> <title>Results</title> <p>Altitudinal ranges for species and genera were correctly inferred even without manual data cleaning and filling. However, erroneous records affected spatial patterns of species richness. They led to an overestimation of species richness in certain areas outside the centres of diversity in the clade. The location of many of these areas comprised the geographical midpoint of countries and political subdivisions, assigned long after the specimens had been collected.</p> </sec> <sec id="geb12326-sec-0005" sec-type="section"> <title>Main conclusion</title> <p>Open databases and integrative bioinformatic tools allow a rapid approximation of large‐scale patterns of biodiversity across space and altitudinal ranges. We found that geographic inaccuracy affects diversity patterns more than taxonomic uncertainties, often leading to false positives, i.e. overestimating species richness in relatively species poor regions. Public databases for species distribution are valuable and should be more explored, but under scrutiny and validation by taxonomic experts. We suggest that database managers implement easy ways of community feedback on data quality.</p> </sec> </abstract> … (more)
- Is Part Of:
- Global ecology & biogeography. Volume 24:Issue 8(2015:Aug.)
- Journal:
- Global ecology & biogeography
- Issue:
- Volume 24:Issue 8(2015:Aug.)
- Issue Display:
- Volume 24, Issue 8 (2015)
- Year:
- 2015
- Volume:
- 24
- Issue:
- 8
- Issue Sort Value:
- 2015-0024-0008-0000
- Page Start:
- 973
- Page End:
- 984
- Publication Date:
- 2015-05-25
- Subjects:
- Ecology -- Periodicals
Biogeography -- Periodicals
Biodiversity -- Periodicals
Macroevolution -- Periodicals
577 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1466-8238 ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1111/geb.12326 ↗
- Languages:
- English
- ISSNs:
- 1466-822X
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4195.390700
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 3169.xml