It’s really interesting to read all the strategies that people take for identifying iNat observations and whittling away at the Needs ID pile. I do think there’s a lot that can be accomplished by people working to ID all the new stuff (or maybe old stuff) within their local area, or all the plants, moths, etc. within that area.
There’s also some value in people trawling through the unknown observations and moving them towards the right Kingdom or Phylum, although that’s an area where I’d like iNat to be automatically nudging new users to add their own IDs:
You recently added 14 observations that have no suggested IDs. If you add a high-level ID like “Flowering Plants” or “Birds” your observations have a much better chance of being seen by knowledgeable identifiers. Click here for a tutorial.
I’ve tried to use both the above approaches, but the one that seems to be most effective and also most rewarding for me is as follows.
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Start by learning the basic ID characters for some particular small group of related taxa, e.g. a genus with 2–5 species, or just part of a larger genus. Let’s call it a “clade”. Understand the range/distribution of each and how they’re distinguished. Get access to a few useful resources (keys, photographic guides, papers in which the species were described or revised).
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Use Identify to search for observations at the genus level for a small portion of the range. Work through the observations, say county by county. For each county, check on which taxa are known to occur there and in adjoining counties. With that info, you can fairly quickly confirm, refine or revise IDs for a bunch of existing observations because the range of possibilities is quite limited. You know what specific characters to look for to distinguish the 3 possible species in this county, for example. Generally, I include all data quality grades (Needs ID, RG and Casual) in my searches because I want to know that I’ve checked every observation of the taxon and make sure I’m aware if my IDs are diverging from those of other experienced people.
Pro tip: If I’m going to exclude reviewed observations in my search, then I’ll often start with the last page of results and work backward. That way, you know that when you’re done with page 13, you can bring up page 12 and see a full page of 30 new observations without skipping any. Working the other way, if you ID 10 of 30 observations on page 1, then when you move to page 2 you’re ignoring 10 unreviewed observations that have slipped past you onto the “new” page 1.
- Once I’ve built up knowledge and confidence with observations already ID’ed to genus level, I’ll search across all or part of the clade’s range working up one taxon level at a time. So I might set Identify to show me all observations in the parent family, but with the lowest rank set to “Family”. That way I can see which of these family-level observations I can confidently move down to genus or species level. If I think there’s a good chance that observations might have been IDed in a sister genus, I might search across the whole family with the lowest rank set to genus. That’s going to pull in a whole lot more irrelevant observations, but might find me a few more that need fixing.
Pro tip: Once I’m at the point where I’m working on finding occasional “known” taxa within a big bucket of stuff I mostly don’t know, I add the setting &per_page=80
to the Identify URL. I find it more efficient to visually scan through 15 pages of 80 observations than through 40 pages of 30 each.
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From there, I’ll keep my search set to the same location range, but back up the taxon rank one level at a time, adjusting the lower bound as I go. As I mostly work with monocot plants, it doesn’t take long before I get to the point that I’m trawling through all Liliopsida, all Angiospermae, all Tracheophyta and all Plantae within the distribution of my target taxa. Mostly, I try to resist the distraction of ID’ing stuff I encounter outside the target taxa, as the work required to check the right references etc. isn’t efficient if these are different references each time. But if you can quickly kick something into Cactaceae or Rodentia, why not?
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Next up is “Unknown” for the same geographic area. This is one I definitely try to process from oldest to newest, as a fair portion of “Unknown” and missing photo observations are still being tweaked by the observer.
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If I’m feeling really thorough, I’ll adjust the search URL from &taxon_id=6345789
to &ident_taxon_id=6345789&without_taxon_id=6345789
. That means that instead of searching for observations that have a particular community ID already, I’m now searching for observations that have a certain identification but don’t have a matching community ID. For example I’ll get a list of everything that someone thinks is a cactus and someone else doesn’t. At this point, the knowledge I have gained should make it pretty easy to add relevant IDs for the real cacti and push a few of the lookalikes in more appropriate directions.
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Last stop will likely be to check out the “Similar Species” that iNat suggests on each taxon page within my self-assigned clade. If iNat reports that lots of people confuse these organisms with Agapanthus and Alliums then I can review those taxa using &per_page=80
to find any obvious mis-IDs.
At this point (or earlier if I lose patience), I’ve IDed the clade as fully as I can and I’ll make myself a note to come back and check for newly added observations in the future. This is the point where I’m ready to broaden my clade of interest, such as to a sister genus, and that takes me back to step 1.
I know my approach allows me to get from zero knowledge to competent identifier in a fairly reliable way, but is it something that would work for other potential identifiers, or is it just too specific to me?