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Global Invasive and Alien Traits and Records (GIATAR) dataset

Authors: Saffer, Ariel; Worm, Thom;

Global Invasive and Alien Traits and Records (GIATAR) dataset

Abstract

Monitoring and managing the global spread of invasive and alien species requires accurate spatiotemporal records of species presence and information about the biological characteristics of species of interest including life cycle information, biotic and abiotic constraints and pathways of spread. The Global Invasive and Alien Traits And Records (GIATAR) dataset provides consolidated dated records of invasive and alien presence at the country-scale combined with a suite of biological information about pests of interest in a standardized, machine-readable format. We provide dated presence records for 46,666 alien taxa in 249 countries constituting 827,300 country-taxon pairs, joined with additional biological information for thousands of taxa. GIATAR is designed to be quickly updateable with future data and easy to integrate into ongoing research on global patterns of alien species movement using scripts provided to query and analyze data. This publication includes: GIATAR dataset files (dataset) Functions in Python and R to join tables and query data (query_functions) Tutorials and example queries in Python and R (tutorials) For more information, please refer to the publication: Saffer, Ariel, Thom Worm, Yu Takeuchi, and Ross Meentemeyer. “GIATAR: A Spatio-Temporal Dataset of Global Invasive and Alien Species and Their Traits.” Scientific Data 11, no. 1 (September 11, 2024): 991. https://doi.org/10.1038/s41597-024-03824-w. Changes in this version (March 19, 2025): Removed base folder from folder structure Included additional files used to update the database Latest records as of March 9 - 10, 2025 Updated species list from EPPO as of February 26, 2025 For continuous updates to code, please refer to our Github repository: https://github.com/ncsu-landscape-dynamics/GIATAR-dataset

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    2
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Top 10%
Average
Average