Inat impact on IUCN red list, upsides and downsides

Nature Talk
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Inaturalist observations are a great source for extent of occurrence or area of occupancy, which are the units of measurement used in one of the categories of the IUCN red list. We can create these maps and asses ton of species that never had enough research done on them on the past and were always data deficient. There is already a research team in Spain working on butterflies thought this methodology, and many more examples.

Brief summary on how IUCN red list works. There are for criteria A,B,C,D with a set of goals to meet for different status. (https://www.iucnredlist.org/resources/summary-sheet). If there is no info to test any of the criteria the species is classified as data deficient. If there is enough info on one or multiple criteria, the species is classified as the most endangered of the different criteria.

Before citizen science, to be able to classify any species on any criteria required a significant amount of research on the species to be able to give it any category. Now species with enough observations can get classified as least concern if they cover enough area, even if we know nothing about their population or ecology.

In my opinion this is a double edge sword. I took Graellsia isabellae as a test subject, download its data from gbif, and made some conservative maps that completely surpassed all the checks needed to be classified as least concern. This means we could classify it as such even thought we don’t know anything about their number of individuals or populations tendencies. It could be feasible for it to have a population reduction enough to be endangered but we just cant know with the actual research on this species.

On the other hand, we can’t classify anything as endangered based on inat observations. To be able to classify a species as endangered due to geographic range we need to prove we have been looking for it but we didn’t find it. We can’t prove Inaters didn’t found species.

I think this will create an influx of species classified as least concern only through one criteria, while the rest are data deficient. Many countries have as objectives of international agreements to reduce the percentage of endangered species, and this could be the gateway to the objective without actual funding or doing work to preserve wildlife.

Maybe its time to revisit these criteria?

Thanks for reading, and mandatory English is not my first language, sorry for any mistakes.

Regards, a concerned biologist.

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This is super interesting, but I imagine raising this concern here will not affect IUCN at all. If your goal is to effect change with IUCN policies, how will a discussion here move that forward? I’m not against people here discussing it, it’s not clear to me what the efficacy would be.

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Im thinking on ways to raise this concern somewhere else, but its something I found interesting, so maybe people here discussing it help me form a better opinion before taking others steps. The nature section of the inat forum is the best forum I know for discussing random stuff about nature.

On the other side I enjoy reading interesting stuff here so I just wanted to provide something in return to the forums members to read

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I think the point you raise has always been a bit of a bias in the way IUCN works. It’s much, much easier to prove presence than absence (if one can even “prove” absence at all).

That said, I agree that iNat (and other cit sci platforms like eBird, etc.) have made presence data much more common than it used to be and increased this disparity of evidence.

One potential approach to this is to have some type of threshold for assessing “likely absence” from cit sci data (essentially all absence data is “We’re pretty sure it’s absent” or “It’s absent from a standardized survey that we use as a criterion anyways).

This could be done in many ways, for instance:

Assessing the number of iNat observations in a place and the lack of a taxon being found there. For example, it’s much more likely something is absent if there are 10,000,000 observations in an area and it hasn’t been found vs only 1,000 observations in the same area.

Researchers could do something a little more sophisticated and assess rates at which similar species in detectability/observability are found on iNat and compare them to the target species of interest to determine whether it is likely a species absent or the absence can’t be assessed due to sampling/detectability.

It would also be worth considering how each criterion is used. I’ve thought the isolated use of criterion B a bit problematic. It’s not too difficult to envision a taxon that can be widespread but threatened through rarity (low density) across its range or a specific threat/s that impacts a taxon across its entire range (e.g., global warming/coral bleaching across large oceanic extents). To me, criterion B is the easiest criterion to assess but the least useful in assessing the true conservation status of a taxon. That said, I don’t think it likely IUCN will change this basic structure anytime soon.

In reality, any attempt to use observational/incidental cit sci data for this purpose will require some careful judgment (how likely is the species to be found and IDed accurately by untrained observers, how much observation activity has occurred in areas where the species would be likely to occur, etc.). But I don’t see anything inherently impossible about IUCN writ large or specific panels/specialist groups devising their own criteria for using these types of data.

One last thought - if something should reasonably be downlisted (i.e., moved to a less threatened category), while some people think of this as a loss of protection, it is good (assuming the downlisting is justified). One of the main points of the Red Lists is to allow for prioritization of effort to taxa that would benefit the most. If a taxon is more widely distributed/less at risk than previously thought, that is good - the limited effort/bandwidth/resources for conservation can be directed more efficiently. It’s also worth noting, that, with minimal geographic occurrence data, it is more likely that rarity/range of organisms will be underestimated. So there has likely been something of a previous bias to overclassifying threat due to range restriction. Adding more data may be a benefit by reducing this bias.

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Not a scientist, but Tony Rebelo has been involved with South Africa’s Red Lists

https://forum.inaturalist.org/t/strange-red-list-status-inheritance/52219

https://forum.inaturalist.org/t/add-red-list-status-to-species-pages-and-observations/52255