Journal ArticleDOI
Spatial bias in the GBIF database and its effect on modeling species' geographic distributions
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TLDR
A subsampling routine is used as an exemplar taxon to provide evidence that range model quality is decreasing due to the spatial clustering of distributional records in GBIF and shows that data with less spatial bias produce better predictive models even though they are based on less input data.About:
This article is published in Ecological Informatics.The article was published on 2014-01-01. It has received 424 citations till now.read more
Citations
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Mapping species distributions with MAXENT using a geographically biased sample of presence data: a performance assessment of methods for correcting sampling bias.
TL;DR: The ability of methods to correct the initial sampling bias varied greatly depending on bias type, bias intensity and species, but the simple systematic sampling of records consistently ranked among the best performing across the range of conditions tested, whereas other methods performed more poorly in most cases.
Journal ArticleDOI
Contribution of citizen science towards international biodiversity monitoring
Mark Chandler,Linda See,Kyle Copas,Astrid M.Z. Bonde,Bernat C. López,Finn Danielsen,Jan Kristoffer Legind,Siro Masinde,Abraham J. Miller-Rushing,Greg Newman,Alyssa Rosemartin,Eren Turak,Eren Turak +12 more
TL;DR: In this article, the authors used the Essential Biodiversity Variable framework to describe the range of biodiversity data needed to track progress towards global biodiversity targets, and assessed strengths and gaps in geographical and taxonomic coverage.
Journal ArticleDOI
Estimating species diversity and distribution in the era of Big Data: to what extent can we trust public databases?
Carla Maldonado,Carla Maldonado,Carlos I. Molina,Carlos I. Molina,Alexander Zizka,Claes Persson,Charlotte M. Taylor,Joaquina Albán,Eder Chilquillo,Eder Chilquillo,Nina Rønsted,Alexandre Antonelli +11 more
TL;DR: Open databases and integrative bioinformatic tools allow a rapid approximation of large‐scale patterns of biodiversity across space and altitudinal ranges, and it is found that geographic inaccuracy affects diversity patterns more than taxonomic uncertainties.
Journal ArticleDOI
Recommending plant taxa for supporting on-site species identification
TL;DR: It is found that occurrence records are complementary to presence-absence data and using both in combination yields considerably higher recall of 96% along with improved ranking metrics, and a spatio-temporal prior can substantially expedite the overall identification problem.
Journal ArticleDOI
Worldwide occurrence records suggest a global decline in bee species richness
TL;DR: In this article, the authors analyzed publicly available worldwide occurrence records from the Global Biodiversity Information Facility spanning over a century and found that after the 1990s, the number of collected bee species declines steeply such that approximately 25% fewer species were reported between 2006 and 2015 than before 1990s.
References
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Journal ArticleDOI
How Global Is the Global Biodiversity Information Facility
Chris Yesson,Peter W. Brewer,Tim Sutton,Neil Caithness,Jaspreet Singh Pahwa,Mikhaila Burgess,W. Alec Gray,Richard White,Andrew Jones,F.A. Bisby,Alastair Culham +10 more
TL;DR: This work investigates the quality and coverage of data digitally available, from the perspective of a biologist seeking distribution data for spatial analysis on a global scale, and presents an example of automatic verification of geographic data using distributions from the International Legume Database and Information Service to test empirically, issues of geographic coverage and accuracy.
Journal ArticleDOI
Incorporating uncertainty in predictive species distribution modelling
Colin M. Beale,Jack J. Lennon +1 more
TL;DR: It is concluded that uncertainty in SDMs has often been underestimated and a false precision assigned to predictions of geographical distribution, and areas where development of new statistical tools will improve predictions from distribution models are identified.
Proceedings Article
Correcting sample selection bias in maximum entropy density estimation
TL;DR: This work studies the problem of maximum entropy density estimation in the presence of known sample selection bias and proposes three bias correction approaches, which take advantage of unbiased sufficient statistics which can be obtained from biased samples.
Journal ArticleDOI
Biodiversity data should be published, cited, and peer reviewed
TL;DR: A staged publication process involving editorial and technical quality controls, of which the final (and optional) stage includes peer review, the most meritorious publication standard in science.
Journal ArticleDOI
The data paper: a mechanism to incentivize data publishing in biodiversity science
TL;DR: The establishment of the 'biodiversity data paper' is proposed as one possible mechanism to offer scholarly recognition for efforts and investment by data publishers in authoring rich metadata and publishing them as citable academic papers.
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