ArticleBio-protocol2023
A Protocol to Retrieve and Curate Spatial and Climatic Data from Online Biodiversity Databases Using R.
Article in Bio-protocol, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Climate Change Effect onEcology and evolution · 2025Article
- High rate of species misidentification reduces the taxonomic certainty of European biodiversity databases of ivies (Hedera L.).Scientific reports · 2024Article
- The interplay between climatic niche evolution, polyploidy and reproductive traits explains plant speciation in the Mediterranean Basin: a case study inFrontiers in plant science · 2024Article
- Evaluation of tropical-temperate transitions: An example of climatic characterization in the Asian Palmate group of Araliaceae.American journal of botany · 2022Article
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Authors and funding
3 authors.
Funding
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Abstract
Ecological and evolutionary studies often require high quality biodiversity data. This information is readily available through the many online databases that have compiled biodiversity data from herbaria, museums, and human observations. However, the process of preparing this information for analysis is complex and time consuming. In this study, we have developed a protocol in R language to process spatial data (download, merge, clean, and correct) and extract climatic data, using some genera of the ginseng family (Araliaceae) as an example. The protocol provides an automated way to process spatial and climatic data for numerous taxa independently and from multiple online databases. The script uses GBIF, BIEN, and WorldClim as the online data sources, but can be easily adapted to include other online databases. The script also uses genera as the sampling unit but provides a way to use species as the target. The cleaning process includes a filter to remove occurrences outside the natural range of the taxa, gardens, and other human environments, as well as erroneous locations and a spatial correction for misplaced occurrences (i.e., occurrences within a distance buffer from the coastal boundary). Additionally, each step of the protocol can be run independently. Thus, the protocol can begin with data cleaning, if the database has already been compiled, or with climatic data extraction, if the database has already been parsed. Each line of the R script is commented so that it can also be run by users with little knowledge of R.
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