I recently went on vacation and had a lot of fun by using a heatmap to identify ecological hotspots I was interested in visiting. I thought I would post the process in case anyone wanted to do something similar, or to get thoughts on how I could make it more efficient.
The process went basically like this:
I got all of the Taxa in the place I was visiting, filtered by the month I would be there, then made a list of all the taxa
I removed all the Taxa I had seen before (common things like mallards, rock doves, etc)
I created an inat link to filter by the list and the region, and book marked it.
Every day I would post observations on inat, then remove those that reached research grade from the list. The bookmarked link generated by the heatmap would then get smaller, and I could look into places with concentrations of species I hadn’t seen before. I found some really cool locations this way, and saw a lot of new species!
I’m mostly curious what people think of this method. Was I over-complicating it? I edited and created the list manually, because I couldn’t find much documentation in the API about how to interact with lists. Is there an easier way to edit the lists? Is there maybe a way to subtract the species from my research grade observations without using the list feature, simplifying the process?
Overall I had a lot of fun with it. It was very cool when I saw a species from out of the typical month (not on my list) or a rare species. I think I gained a lot of familiarity with the biodiversity because I was often looking at the list.
You have the right process, but there is a URL modifier that streamlines it considerably that you could have used. It is unobserved_by_user_id. Append “&unobserved_by_user_id=melspippin” to an iNaturalist URL in a web browser to filter to only observations of taxa you have not observed.
you can use that in conjunction with what rynxs mentioned to see places with higher absolute numbers of observations of taxa that you’ve never seen before.
i don’t totally understand why you’re starting off your process with a list of the taxa in the place you’re visiting, filtered by month. maybe the filtering by month just reduces the number of taxa that you have to put into that list initially? (otherwise, it would make more sense to filter by month in step 3, in my mind.)
you can batch upload to lists using the iNat user interface, but you can also use POST https://www.inaturalist.org/listed_taxa with a JWT to add stuff. i don’t think that’s formally documented anywhere, but you can just open up your browser’s developer tools and look at the network monitor to see what the screen does when you add a taxon to a list, delete a taxon, etc.
Thanks this helps a lot!! Do you know if this takes into account research grade vs not research grade? Also how this works with things above species (for example if I have some labeled as “Cetaceans”, will that remove all observations just at the level or anything below that level. I guess I wouldn’t want to remove anything from the list unless it was confirmed.
I think the filtering by month was just to reduce the volume added to this, which from the other comment seems like maybe not the most efficient method.
For the heat map you linked, just to make sure I’m reading your documentation correctly “red” would be the places where there are more obs I haven’t seen?
It only factors the specific taxon rank of the observations, so you don’t need to be concerned about that. For example, if I have two observations, one at Kingdom Animalia and one at Orcinus orca ssp. rectipinnus, all species-rank observations of Orcinus orca will still show as unobserved taxa because I do not have an observation at the species-rank taxon Orcinus orca.
You can add a filter for research grade observations yourself with the quality_grade=research URL modifier.
it’s not exactly a typical heatmap, but for this visualization, red is one end of the scale and blue is the other, with green in the exact middle. this means that red would indicate 100% observations of unobserved taxa, blue would indicate 0% observations of unobserved taxa, green would indicate 50% observations of unobserved taxa, yellow would indicate 75% observations of unobserved taxa, and cyan would indicate 25% observations of unobserved taxa.