The issue with this is it requires micro level range information to be meaningful. It is all well and good to tell someone (assuming they even look at it) that for example Leucorrhinia dragonflies can be difficult to separate visually. Someone where I live doesn’t need to know that, realistically they are only going to encounter 2 species, which are easy to separate. If they live 300km north of here with 3 or 4 species, or 800 kilometers north of here with maybe 6 possibilities it is important information.
Telling someone here where I live, in the same province (ie the provincial checklist is worthless when your province is 5 times the size of the United Kingdom) that information is counter productive.
The only realistic way to manage this level of micro range information is through the observations themselves. Which means dealing with those. And getting Seek and the iOs app to parity in terms of defaulting to presenting options seen nearby.
I can see this being helpful for monotypic (or regionally-monotypic) genera, especially those whose genus is also the common name, that are often identified only to genus level. I spend a lot of time adding IDs for Sassafras > Sassafras albidum, Galax > Galax urceolata, Oxydendrum > Oxydendrum arboreum, etc.
Joining this party a bit late as I was thinking a similar thing and brought it up on another thread.
I was thinking more of an automatic threshold (which someone has mentioned above). I don’t know what the threshold should be: something like 10% or more of observations originally identified as this have disagreeing IDs. Then a red exclamation mark appears next to it on the suggestion dropdown - hovering over it brings up the message “This taxon is frequently identified in error: if you are uncertain, consider selecting the genus instead.”
Better to stay with a human ‘flag for curation’ and a human ‘flag as problem taxon’.
Automated will add yet another layer to be cleared by a taxon specialist.
Sorry, I really don’t understand the point you’re making here. How would automation create more work for a taxon specialist? Surely it would do the opposite by definition…
Asking a taxon specialist to do it themselves as you suggest would give them more work - doing it for them automatically would give them less…
This can be a big issue. For example, looking down the US records of Lysimachia foemina (Blue Pimpernel) almost all of them are mis-ID’d (should be L. loeflingii) - about 400 records, which includes RG ones. If one looked further than the US, vastly more.
How long would it take to go through 400 records - or thousands - and ‘fix’ them? a long time!
How long would it take to add a note, so that when someone chooses L. foemina the note appears clearly in red between their choice and their comment box, saying “Caution: most L. foemina records are L. loeflingii, which has broad not narrow petals - (link: learn more)”? a few seconds! It would cause most people to change to L. loeflingii and save masses of correction time, and also help with their learning. This is also an AI problem since the AI always shows people L. foemina, but then it’s a vicious circle as the AI probably then learns from the RG records which are wrong.
To implement would need to allow geo notes for a taxon, and on selecting a taxon would select the note which the observation geographically fell in having the smallest area (so on adding an observation for the UK if there is a note for both UK and Europe, both match geographically but as the UK has the smaller geographic area it is picked, this area size being calculated at note entry and so prestored).
Programmatically this is fairly easy assuming the existing functions that already can detect an observation is in an area, but even just rectangular or circular areas or a multiselect country list (perhaps ideal since people tend to know taxa by country and the observation location seems to have already been decoded to country) would be quite servicable. Functionally it would be incredibly useful.