How do I handle images of 1 plant across time? For instance, in spring I often see a plant that Seek can’t identify beyond “dicot”. I’ll upload to iNat in hopes for an ID. Then summer will hit and I’ll take more pictures. Then autumn, I’ll take more pics. Should I be creating a new observation or adding the images to the original observation? I feel like adding it to the original observation makes more sense because a user can see all stages of growth for identification.
I would record each as a separate observation, use the “similar observation set” field to associate them, and put an explanation and link to the original observation in the notes for each subsequent observation. These make great sets of observations.
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Welcome to the Forum. I don’t have much to say, other than documenting a plant, or whatever, over time is extremely valuable. Some folks have done it with insects, too. Others may have more concrete details about how to do this.
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You should record each as a different observation.
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Sounds like a good method, but what is the “ similar observation set” field?
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There are a couple of tricks that can be used to create a “similar observation set” or “linking group”, but the easiest is to make multiple observations, one at each time point, and then add a link to the related observations in the description. I tried one like this here, although I did it sloppily and it never did get conclusively identified.
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If I make an observation of a plant flowering I will often go back a while later to the same plant to photograph the fruit. I use the “Related observation” observation field as well as manually editing the location data so that they match exactly
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Here is the forum post where I first learned of it and how it can be used.
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That makes sense, but iNat really isn’t suited for abundance type analysis, so I don’t see that as a concern.
Bioblitzes, for example, result in hundreds of ‘duplicate’ observations (same organism, different observers), and it’s common for a photo to be taken of a flock of birds treated as a single observation.
iNat is best suited to presence/absence type analysis.
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Actually, this was the observation I was looking for - Genus Narina from Pringle Bay, 7196, South Africa on August 06, 2017 at 09:37 PM by magriet b. <h3>Ambush life in a tub</h3> <h4>6 Aug 2017:</h4> I collected an adult ambush bug with 10 eggs … · iNaturalist.ca
I thought this was a good way of handling at least an insect life cycle.
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I’d be very wary of using frequency of observations in an area as a proxy for actual abundance in the wild. It’s tempting to do so, and it makes sense at first glance, but it ignores the fact that iconic and easy to see species/individuals wind up being massively over represented.
An example, in the area I work there is an island where macaques of various species were dumped back in the 90s to attract tourists. Tour boats bring people to that island on a regular basis, and they have a massively higher observation record than their actual population deserves.
Same with the black kites in our region. They are numerous, but there are many other birds that are more numerous, but they’re most difficult to see, or to get photos of, compared to the slowly circling black kites, so the kites get over-represented in the observations.
Colorful, obvious, iconic, etc species are vastly over represented in many areas and skew the observation results.
Even using location to filter doesn’t really help as people are often not terribly precise in their locations, and people tend to go to the same places, so you get a lot of observations in one area, but not in an adjacent area. And that area people go is usually chosen for some specific reason (eg. for nature tourism because it has something special and unique to see).
The example of bioblitzes was just that, an example, meant to illustrate a point and demonstrate how observations in general get skewed. It wasn’t meant to be taken to mean that bioblitzes by themselves are responsible for the majority of duplicate type observations altering abundance data.
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It’s more that it gives a very incorrect view of the relative abundances of species.
And in the case of the macaques here, given that we know exactly how many there really are on the island, yes, the observations massively overrepresent them in terms of absolute abundance as well.
It’s one of the observation fields that exist already. It will ask for an observation ID to link them all together. This is the number at the end of the URL. I usually try to use the first observation in a series to get this number from. Once linked together in this way, it lets you pull up all the observations with this field (example). I think it was originally designed for raising insects through metamorphosis, but I like to use it for plants observed during different seasons and as a way to track phenology over the years.
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Observing the same individual at different times can provide a useful record of phenology, of molt progression, of survival, etc. It’s great. To be maximally useful, the records should be tied together in some way. I’ve just been using notes about what other observations are involved, but I’ll to figure out this similar-observation field.
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I agree with the several responses welcoming your suggested approach, @tnich - and the use of an observation field like “similar observation set” or “Observation group”. I use the latter with the iNat observation number of the initial observation to connect an individual tree with the insects I find depending on it, e.g. in galls. I add a link to it as a comment. - I’ve limited myself a lot on plant observations when it seemed unlikely to be identifiable due to (apparently) insufficient features. I feel your procedure is the solution that lets me learn more about plants. The number of such observations will be limited simply because it takes some effort to keep track of the individual plants.
That said, I can understand bdagley’s concern about watering down his abundance analysis method because I’m also more interested in aiding research than enjoying pictures. Though, it seems to me that the situation is quite different for plants than for insects. I can see that meaningful abundance information may be gleaned from iNat data for insects. The huge diversity of insects and the limited time interval during which many of them appear should have a randomization effect. - I’m not sure if anybody uses iNat data to analyze plant abundance in a similar way.
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I’ve planted a bunch of native plants on our land in addition to a bunch of naturally occurring ones that came in on their own. I know where they are and watch them throughout the year and it’s been incredibly helpful in my ability to identify these species elsewhere during the off season. I haven’t put them all in inat and honestly someone would probably tag them as no further ID needed and knock the taxonomy back because I couldn’t identify them either without knowing where they were. It would be a neat project though. I’ll bet it would be possible to pick out differences in the first sprouts of even difficult taxa like solidago.
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You probably want to check out the Plants Out of Season project, it looks for exactly this sort of info – what a known plant looks like on its “off season” or basal stages.
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Ooh I will thanks
I come down strongly on the “You can’t use iNaturalist data to estimate abundance” side of the argument. Not that it’s never possible, but you need many qualifications and assumptions about the number of observers, what the observers photo, the likelihood of species X being photo’d if present, etc. I think iNaturalist is great for presence/absence information and for some things duration (earliest, latest, etc.). Not abundance.
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Imo the only downside is how map will look, no matter if many people see things at once, or one person throughout time, especially considering how observations are rarely aligned with each other, I don’t bother specifically about abundance which won’t ever be true because of humans, but it just creates a false impression about this particular spot and e.g. number of mature or juvenile specimens that appear there, especially if observations are not from one day, you can imagine there being a forest when there’s a single tree, or it can affect observer too, as looking at map of their observations, they will see like ten oaks in this spot, which could make them feel they observed already enough oaks in the area (sure, if you do that with one plant only, chances are less, but still even when you know it’s that particular plant, your brain still falls for many observations you made), so this could lead to less observations of more individuals while more individuals at one time is a more interesting (useful for iNat) data.