New feature: download lists of distinct species contained in occurrence searches

Data Use
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Ever wanted an easy way to create a list of all plants with GBIF occurrences in Brazil—or insects in South Africa? Please keep reading…

New download format added

Since the launch of the current GBIF.org portal, users searching species occurrence data in any temporal, geographical or taxonomical contexts have been able to view an ordered list of species present in the search result by visiting the Taxonomy tab—e.g. mammals in Denmark.

We’ve now added the ability to download a list of taxa present in any given occurrence search. It works just like ordinary occurrence downloads, only instead of choosing CSV or Darwin Core Archive, you choose Species list as CSV:

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Once the download archive (example) is ready, you’ll get a notification as per usual, and once you’ve downloaded and unzipped the archive, you’ll have a CSV file—excerpt shown here as a table, sorted by number of occurrence records:

taxonKey scientificName acceptedTaxonKey acceptedScientificName numberOfOccurrences taxonRank taxonomicStatus
5220126 Capreolus capreolus (Linnaeus, 1758) 5220126 Capreolus capreolus (Linnaeus, 1758) 56575 SPECIES ACCEPTED
7952072 Lepus europaeus Pallas, 1778 7952072 Lepus europaeus Pallas, 1778 38321 SPECIES ACCEPTED
2436736 Lepus capensis Linnaeus, 1758 2436736 Lepus capensis Linnaeus, 1758 31975 SPECIES ACCEPTED
2434793 Phoca vitulina Linnaeus, 1758 2434793 Phoca vitulina Linnaeus, 1758 24310 SPECIES ACCEPTED
8211070 Sciurus vulgaris Linnaeus, 1758 8211070 Sciurus vulgaris Linnaeus, 1758 21509 SPECIES ACCEPTED
2433753 Lutra lutra (Linnaeus, 1758) 2433753 Lutra lutra (Linnaeus, 1758) 17655 SPECIES ACCEPTED
5219243 Vulpes vulpes (Linnaeus, 1758) 5219243 Vulpes vulpes (Linnaeus, 1758) 16712 SPECIES ACCEPTED

One thing to notice is that the list contains rows for all names with occurrences including e.g. synonyms and organisms identified at higher taxon levels. In the case of my Danish mammals list, this means that I’ll also see entries like:

taxonKey scientificName acceptedTaxonKey acceptedScientificName numberOfOccurrences taxonRank taxonomicStatus
2439140 Clethrionomys glareolus (Schreber, 1780) 5706764 Myodes glareolus (Schreber, 1780) 3056 SPECIES SYNONYM
734 Chiroptera 734 Chiroptera 1597 ORDER ACCEPTED
4941589 Pinnipedia 4941589 Pinnipedia 664 FAMILY ACCEPTED

What do you think?

We’d like to invite everyone to try out the new feature and let us know what you think by posting a comment in this thread. If you notice odd behaviour or bugs, feel free to report using the Feedback button or directly in Github.

Thanks!

2 Likes
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Super!
In just 2 clicks and a couple of minutes, I got a list of 13.590 plants occurring in Belgium, of which 5.048 with more the 10 occurrences.
Cannot wait to compare with Species.be 2.633 plants species.

1 Like
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Super useful! Does anyone know if this available through the occurrence API?

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Yes it is! You can get a species list via the download API: GBIF occurrence API. You just need to set the format to SPECIES_LIST.

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Super cool! Is there a way to filter species not naturally occurring in the selected location? For example, I select occurrences for some clades of plants occurring in Europe but I do get a lot of species that are not naturally occurring here and are likely to be observations from botanical gardens, private collections or similar.

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Hi @josebsl

There isn’t really any easy way to do that but there are a few things you can do:

  • You can remove fossils and living specimens from your occurrence selection (the living specimens correspond often to botanical gardens and zoos)
  • You can also try to filter occurrences by establishment means (for example native species). However, this relies on data providers sharing the information. Most occurrences don’t have a value for that field and wouldn’t be included in such selection.
  • You can exclude species that you know are introduced in the region. For that, the Global Register of Introduced and Invasive Species checklists can be helpful.

If you are an API or R user, this blogpost can help you refine your selection.

I hope this helps!

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