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

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.