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Global Country Checklists for Odonata

Wednesday, July 6, 2022


A figure from the Sandal et al. paper 'Country-level checklists and occurrences for the world's Odonata (dragonflies and damselflies)'. The figure is titled 'Species Richness' and shows a world map in the Mollweide projection with countries colored from dark blue to red. The figure legend shows that these colors correspond to species richness in the countries.
Figure 1 from Sandall et al.


In a study led by Yale BGC postdoc Emily Sandall and co-authored by former postdoc Stefan Pinkert and Walter Jetz, the most comprehensive global-scale dataset of odonate distributions available to date has been recently published and the data made freely available at MOL.org! Through a rigorous assessment of literature-published odonate checklists and point occurrence data from GBIF, as well as a novel approach to interpolating missing species-country combinations, they developed robust, up-to-date dragonfly and damselfly checklists for all countries!

To compile these country checklists, Sandall et al. performed a spatial cleaning of the occurrence data and a taxonomic harmonization of the raw species names from the literature and point data against the MOL Master Taxonomy for odonates – a crucial step in synthesizing large biodiversity data. To account for gaps in the published data, they additionally interpolated likely missed species in undersampled countries, resulting in a grand total of 31,569 unique species-country combinations in the final country checklists. The authors anticipate that gaps in this baseline dataset will be filled as more checklists are updated and more species described.

This dataset provides crucial baseline distributional data for odonates, a much needed update from the most recent work in odonate biogeography published over a decade ago. Sandall et al.’s work developing these checklists will have important contributions to regional, national, and intergovernmental efforts to effectively assess and manage dragonfly and damselfly conservation. Read the paper here and explore the dataset here!