A class in Hong Kong is uploading a ton of observations of cultivated trees. I’ve already reached out to the project owner, but perhaps the damage has been done. I’ve marked quite a few so far.
In case anyone wants to help mark these captive/cultivated:https://www.inaturalist.org/observations/identify?place_id=7613&taxon_id=47126
OK, did a couple pages for a tiny dent. Not all showed enough context to be definitively planted.
Could the iNat computer vision be used to help mark obviously cultivated stuff?
It could even notify the user as “your observation has been marked as “cultivated/not wild”” or something.
I’m curious what about this situation made you create this thread, @tiwane . Is there some reason why you are more worried about these unmarked cultivated trees than other typical class projects with a “flood” of unmarked cultivated plants? Is it the volume? The location?
Because of their long lives and their value to humans, I often have trouble determining whether a tree is planted or wild, even when I am the observer.
Were the ngaio trees along the edge of the bay planted or did a bird drop the seeds? Did the rancher plant that oak before the ranch became a preserve? Often there is no way to get a definitive answer.
Surely anyone researching the distribution of trees recognizes this.
The other “problem” with trees is that people really want to know what species of trees are planted in their neighborhood. When people post tree species I don’t know, I often wish iNat had a project for mapping planted trees, with a crew of knowledgeable people to help identify them.
Maybe it’s time to accept that trees are special?
At the risk of rehashing this subject (which has taken place several times on multiple different topics) I suggest we stick to dicussing the original post here.
there should be the possibility to temporarely block a project by site admins whenever it is becoming obvious that things are getting out of hand
Probably because it was late on a Friday night and this is what I was doing with myself at the time. 
Also, there were a ton of them, so scale was part of it, and I have some residual flashbacks to the Penang situation. I didn’t know how large it might have grown.
Yikes. That was before I got here. Now I see where all the hate for “duress users” comes from.
That actually is not considered a case of duress users, all those folks were using the app of their own choosing. Duress users are usually defined as students assigned to use iNat as part of their coursework who would normally never touch the site or app.
I think that in most cases it is not a matter of hate towards users that actually often are rather young and thus deserve all the necessary patience. Differently, it is possible that in many cases teachers and projects creators and adminitrastors should be kindly blamed and asked to put all the necessary attention to exhaustively explain how to and how not to use the site…
When a “flood” of unflagged observation occurs, fixing the issue often turns out to be a time-demanding activity.
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