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A Protocol to Retrieve and Curate Spatial and Climatic Data from Online Biodiversity Databases Using R.

Marina Coca-De-La-Iglesia1,2, Virginia Valcárcel1,3, Nagore G Medina1,3

  • 1Departamento de Biología, Universidad Autónoma de Madrid (UAM), Madrid, Spain.

Bio-Protocol
|October 30, 2023
PubMed
Summary

This study introduces an R language protocol to automate the processing of spatial and climatic biodiversity data. It simplifies data preparation for ecological and evolutionary studies, making high-quality biodiversity data more accessible.

Keywords:
BIENBiodiversityClimateData cleaningDatabaseEcologyGBIFR languageWorldClim

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Area of Science:

  • Biodiversity Informatics
  • Computational Ecology
  • Bioinformatics

Background:

  • High-quality biodiversity data is crucial for ecological and evolutionary research.
  • Existing biodiversity data is fragmented across online databases, requiring complex preparation.
  • Manual data processing is time-consuming and prone to errors.

Purpose of the Study:

  • To develop an automated protocol in R for processing spatial and climatic biodiversity data.
  • To streamline data acquisition, cleaning, and integration from multiple online sources.
  • To facilitate biodiversity data analysis for ecological and evolutionary studies.

Main Methods:

  • Developed an R script to download, merge, clean, and correct spatial biodiversity data.
  • Integrated climatic data extraction from sources like WorldClim.
  • Implemented filters for data cleaning, including range validation and spatial correction.
  • Utilized genera from the ginseng family (Araliaceae) as a case study.

Main Results:

  • The protocol automates the processing of spatial and climatic data for multiple taxa.
  • It successfully integrates data from GBIF, BIEN, and WorldClim, adaptable to other databases.
  • The cleaning process effectively removes erroneous and out-of-range occurrences.
  • The script is modular, allowing independent execution of data cleaning or climatic data extraction.

Conclusions:

  • The developed R protocol significantly reduces the time and complexity of biodiversity data preparation.
  • It enhances the accessibility and quality of data for ecological and evolutionary research.
  • The protocol is user-friendly, with commented code suitable for users with limited R experience.