Hi, newbie here.
If I record every instance of a species I see, Rowan for example, is this useful to the project? Should every tree / plant be mapped?
It strikes me that close to where I live there should be lots of logging of some species, Common Bracken / Common Heather / Bell Heather for example, which would map their range if enough iNaturalists contributed.
Or am I not thinking this through? Please be gentle :-)
Sometimes people will do a survey of a region or even a city block and everyone is asked to just identify everything in the target group. This can show population densities and patterns of distribution.
As an individual observer I think you should record what you find significant. I will jump to log a new ant species I’ve never observed before because it’s new to me. I might also make an observation if I see a species in a new place where I didn’t know they might be found. I might make an observation because the ants are doing something special like a nuptial flight.
I’ve only just started using iNaturalist for this but that’s how I look at my own records.
One time I wanted to know what ants lived on a particular oak tree, so I made remarks about every ant if I could establish it was from a separate colony. I used this to write about how amazing oak trees can be in cities as little islands of biodiversity. I should have used iNat for that, it could have been fun. Maybe I’ll do it again.
This question has been discussed many times on the forum. You can find the threads in the “Related topics”, below. Here is one previous answer:
Not a silly question — and I would push back gently on the framing that it depends only on your goals. Sometimes the data turns out useful in ways nobody planned.
We run a small camera-trap project in the Atlantic Forest of Brazil (Vem Pra Mata). The camera photographs the same pigeons and the same opossums night after night, and I nearly stopped uploading them because it felt like noise. I am glad I did not. Repetition is what turns records into data: one observation says a species exists here, while a hundred across a year show when it breeds, when the young appear, how it responds to the seasons. For plants that is even stronger — the same rowan photographed in April, June and October, with the phenology annotations filled in, is worth more than three different rowans photographed once each.
And common species are precisely the ones with the weakest baselines. A decline only becomes visible if someone was documenting the species while it was still abundant. Bracken and heather feel unremarkable today; that is exactly why they will matter later. In our case the opossum is a thoroughly ordinary animal locally, the kind nobody photographs on purpose — and our small project has ended up holding a meaningful share of that species’ records on iNaturalist, entirely by accident.
One practical caution: several frames of the same individual in a single encounter should be one observation, not twenty. The same individual on a different day is a legitimate new record. Beyond that, record freely, fill in the annotations, and do not apologise for the ordinary.
Inherent Biases
Something to bear in mind is that you can’t record everywhere - not in people’s back gardens, nor in most fields, nor in the greater part of woodlands - so recording will introduce biases. Recording at greater intensities will exacerbate the biases - recording which grid square a species in present in will give biases to urban areas, and rural areas with good footpath networks, and country parks. Recording at higher resolution exacerbates this. Imagine dividing a grid square into 100 hectares. Locally to me I can access roughly 20 to 100 of those hectares, the upper end being wholly built up areas, but I don’t have to go all that far (about 20km) to find grid squares which are inaccessible, and I could only record large plants visible and identifiable at a distance, or none at all. Recording to grid square level is not too bad at mapping the overall distribution of a species; recording to hectare level results in mapping accessibility rather than plant distribution.
Personal Policy
My personal general rule for unvouchered recording (no physical specimens nor photographs) is one record per species per grid square per year, with repeats allowed on subsequent days for different sites and different flowering status. Multiple records of rarer plants are taken to allow them to be refound, and to allow recording of rarer variants of species.
Discussion of example taxa
At the one extreme, I’ve seen fields covered with Urtica urens. Recording every plant there would clearly be ridiculous, as well as impracticable. A practice that is recommended, but which I am mostly guilty of not following, is to record the number of plants at a site, switching to “many”, “hundreds”, “thousands” at some point.
At the other extreme, recording every amenity street tree (mark them as cultivated in iNat) in an area seems a not unreasonable project. For amenity shrub borders I would record the species (also mark as cultivated) present in a border/set or borders, rather than individual plants, possibly with duplication if a grid square (monad) boundary is crossed.
In the case of bracken, what is a plant is unclear. Bracken is rhizomatous; while shoots look like individual plants they grow from a common root system, and quite expansive patches of bracken can be clonal. Recording the location and estimated size of each colony of bracken could be done; that allows investigation into the ecological aspects of distribution, rather than just the geographical aspect. For Japanese knotweed people are probably interested in the location of every colony - for control purposes - but there is one country estate garden I know which has clumps scattered around the site, and I haven’t gone to the extent of recording every clump there.
A moorland full of heather has even more plants than a field of Urtica urens. One country park near me has small colonies scattered around it, and I have gone so far as to record individual colonies, rather than just grid squares. But when you get to a moorland, field enclosure or grid square for unenclosed moorland seems a reasonable resolution.
In my neck of the woods rowan mostly occurs as bird sown seedlings probably originating from cultivated plants. Plotting the locations of cultivated and bird sown plants could potentially be used to investigate seed dispersal. (A related species, Sorbus croceocarpa, occurs as old trees in a number of Victorian parks, but presumed bird sown specimens turn up great distances from those locations, so I suspect that a project with rowan wouldn’t work out - you’ld be investigated establishment rather than dispersal.) But rowan also occurs as wild populations in the understorey of birch-oak woodlands, and also moorland streams and other moorland sites protected from grazing. A woodland could potentially contain 100s of rowans.
Tradeoffs
Finally, you have to take the time cost into account. In the summer I can generate 100 unvouchered vascular plant records in a hour (20 in 5 minutes, but diminishing returns kick in), possibly 120 to 150 if I picked the right location (and maybe 300 if I automated GR recording and allowed duplicates); with the iNat app the number is about 20 (if it doesn’t lose internet connection) and with the Seek app maybe 40 or 50. Recording particular species at high intensity means compromises with recording more species, and recording a greater geographical spread.
If I started doing observations of trees should I check if that tree has been recorded before? Many NYC trees have a QR code where you are supposed to be able to look up the species… but many of the codes don’t work (program is from like 10 years ago)
But, wouldn’t it be neat to add to an existing observation of a notable tree, provided you could geolocate it and verify it was the same one? Is it still alive? Did it grow? What ants are hanging out there today? That would be awesome.
This is a great question, thank you for asking. I appreciate the responses too.
For myself, there are reasons I will record many of the same species in an area or areas - if it is something that hasn’t been seen in a few years, or in low numbers only for a few years, I will record a species every 15 meters in the rare area it is found to show a history of its abundance in that space.
This data was very helpful through 4 years of recent drought where few if any of the plants were found where they used to be, and then this being a wet year, they are back in the pre-drought abundance.
I do something similar with galls - when found I record one per area (a square kilometre) to show how far they have spread. I will often note 'few, many, or tons of them" in the description.
Record every dandelion - not a chance. Record a dandelion in an intact forest that had none last year - for sure - and make sure I wash my boots better in case it was me that brought it in!
@lavateraguy makes the strongest point in the thread, and it is worth sitting with: at fine resolution you often map accessibility rather than distribution. That is true of nearly all opportunistic recording, mine included.
Camera traps are one of the few partial exceptions, which is why I keep uploading the repetitive records. Sampling effort at that point is constant — the camera does not get tired, does not prefer charismatic species, and does not skip rainy nights. The bias is different rather than absent (it is a single fixed point, chosen by me, and biased toward whatever walks past at animal height), but the effort is at least uniform through time, so seasonal patterns in the data are more likely to reflect the animals than my walking habits.
@myrmepropagandist — on returning to the same individual tree, iNaturalist does not merge visits into one record; each visit is a separate observation. The usual approach is an observation field such as “Individual ID” with a consistent label, which lets you retrieve the series later. We are running an informal pilot of exactly this with a handful of trees, photographed weekly with phenology annotations, and no physical tags yet. The honest finding so far is that the limiting factor is not the platform but whether the weekly routine survives contact with real life. If it holds for a season, tags and identifiers follow; if not, better to have learned that cheaply.
Do what you enjoy, but my thoughts are, it depends a lot on how many of the same species we are talking about in an area.
If mapping the locations of every Rowan in a park that has fifty of them is interesting to you, by all means go for it. You can even observe them again once a year, or in different seasons.
But if you see a field with thousands of plants of the same species, posting them all as separate observations would create tedious work for identifiers (someone needs to agree with your ID before the observation becomes research grade) and take their time away from other observations that also need attention.
What I would suggest there is to make just a few observations of representative individuals from the location, put in the notes that there were thousands, and include a habitat shot to prove it. Someone studying changes to the site decades from now can still use that record to see about how many there were, even if only one of them was officially “the observed organism” on iNat.
That isn’t necessary. An iNat observation records an interaction between one person and one organism at one time, so even if you were walking with a friend and saw the tree together, you could both post observations of it. Or you could post the same tree again yourself in a year, or some other interval of time that makes sense to you. Though if you meant should you check just so you can see who else recorded it or how it has changed over time, sure! That might be interesting, and maybe you could link to the other observation in your notes.
If you still have the records from that, maybe you could make an iNat journal post about it.
This may be an unpopular opinion, but I feel that posting observations of many individuals of the same species at one location creates a burden for identifiers and doesn’t really add to the scientific value of the entire collection. If there is variability in the organisms and you want to show a range of characteristics, that’s fine, but iNaturalist isn’t really set up for detailed statistical analysis of populations over time. There’s too much variation in how people use the platform. I mostly identify birds, and firmly believe that it you want to report species counts that can be used to derive status and trend data, use eBird.
Hi, @yorkshiresoul! Welcome to the merry madness.
I offer a counterexample to the very good points previously made. My passion is for Odonata—dragonflies and damselflies. I also live in Colorado, which has more species of odes than many people think. Because the lifecycle of dragons and damsels is so intimately tied to water, and because Colorado is not exactly known for enormous wetlands, ode species here are really good at colonizing any remotely usable water source. I tend to document any individual that holds still long enough (and many who don’t) in order to get a picture of year-to-year variation in populations.
Which brings me to this summer.
Colorado had a frighteningly dry and warm winter, with the lowest recorded montain snowpack ever. Most of the lakes and ponds in the Denver area were ice-free by early March. Then there was an early warm-up in the spring, followed by a sudden cold snap and some of our missing snow. Odes who emerged early didn’t stand a chance. This summer has seen record-setting heat, with high pressure domes blocking the usual July moonsoon. Ponds that were already stressed are either drying or empty. I haven’t even been able to get out to survey most days this summer because it has been too dangerous to do so.
The days that I have been able to manage outdoor time, it’s been hard to find odes. Reliable spots have seen population crashes, which I wouldn’t have known about if I hadn’t been so compulsive about documenting previous densities. I’m worried that certain populations have been completely wiped out, but I won’t know until I can get back to those spots without risking heatstroke.
Point is, my obsession has allowed me to build a baseline picture of what ought to be there, and generally in what quantities. From a conservation perspective, this is beyond valuable.
Just my $.02. 
To get a taxon to be learned by the CV. Yes, I would say very.
Funny, I’m the top identifier of Chironomidae on the site by such a large margin, if i recall the next 40 chiro identifiers combined are still smaller than my number of chiro IDs.
I just posted 30+ observations of a single chiro genus from around the same time frame, hopefully I’ll add 30 more. This is solely because i want the genus to be learned to help improve the CV and reduce misidentifications.
Depends on the goals of the project. Personally, I should think that if you are recording biodiversity for a specific place over a specific period over specific times of the day etc etc, then by all means. I have been in places where another one of these https://www.inaturalist.org/taxa/593485-Ruschia-intricata scratching my poor bare shinbones was just a meh experience, because there were just so many of them. On the other hand, now there is at least data for the area showing that these are endemic and plentiful. I’ve been known to get tired of doing urban walks in the Western Cape and recording instances of https://www.inaturalist.org/taxa/76764-Echium-plantagineum because they are in virtually every field and protected environment now, but I do think it is vital that people know that an introduced species can spread very fast and hence the more data the better.
Of course, if you get tired of photographing Rowans, you can always try to look for insects, lichens and galls on them and photograph those as well to show interactions and to help combat those “ugh another one” moments.
Posting on iNaturalist is not the only way of recording wildlife. If you want to do a population study involving hundreds of records of the same species, that could be an interesting and useful project. But consider writing it up for a natural history journal rather than keeping all the data as iNaturalist observations.
I’m a pretty active identifier and I don’t mind lots of observations (even hundreds) of the same species on the same day at the same spot. For everything other than birds, there’s no easy way to make it obvious where there’s a concentration of, say, a certain uncommon species. I know that people who specialize on galls and leafminers then use such data to find the species that colonize particular plants, for example.
Notes and observation fields are fine, but just not as quick to find and access as simple concentrations of observation points in a small area.
Yup. I don’t have quite the same margins as you, but there’s a reason that The Doctor refers to me as the Queen of the Plains Forktails.
@lynnharper’s point about concentrations of points being easier to spot than fields or notes is well taken — and it makes me want to raise a related problem from the other side of the fence.
I run a camera trap in the Atlantic Forest. Everything @lavateraguy said about accessibility bias applies to me too, but inverted: my sampling effort is constant while my spatial coverage is a single point. Hundreds of records within a ten-metre radius. To anyone downloading the data, that reads as a hotspot when it is really just one camera that never sleeps.
The one thing I am reasonably confident about is the treatment of bursts. An opossum passing the camera triggers a rapid sequence of frames, and I treat that sequence as a single observation. When the same species reappears half an hour or so later I treat it as a separate encounter, since I have no way of knowing whether it is the same animal — a presumption about independent detections rather than a claim about the individual. A pair of wood-rails showing up together in one frame, after months of my assuming it was a single resident bird, was a useful reminder of how weak my assumption was.
Beyond that I am genuinely unsure, so a question for the identifiers and data users here: what would actually help you tell camera trap records apart from ordinary opportunistic observations?
There is a Camera Traps (Trail-cams) project, and its curator has written about spending a great deal of time hunting for such records manually because most people add no keywords at all. So a convention exists but seems little adopted. Is joining that project the accepted signal? Is there an observation field people already rely on? Or is none of this worth the effort from your side of the data?
I ask because I would rather be useful than be noise, and right now I do not know which I am
As a newbie, I think it’s far more important to concentrate on developing your skills as a naturalist than worrying too much about whether what you’re doing is useful. In the long run, almost every observation you make will be valuable to some future data-consumer. Let them worry about the statistical significance of your data, and just focus on enjoying nature and becoming a better naturalist.
There’s only twenty-fours in each day. The time you spend on recording every instance of one species, is time that you can no longer spend on other species. Just think of what you might miss! When many things are new to you, it’s always worth spending some extra time looking a little more closely at each specimen. It can be very easy to overlook the subtle differences that may mean you found something you’ve never encountered before. Quality is often much more important than quantity when you’re still learning
As a general rule, it’s usually good enough to simply record presence rather than attempting accurate counts. At the very least, this should always contribute positively to the maintenance of species atlases, which is one of the most important functions of iNaturalist (and most other nature recording projects). If you’re recording in the UK, a good general plan is to focus on under-recorded monads (i.e. 1 km squares) within your local vice-county. Aim to fill in as many squares as you can with just a few records for each species per year, rather than attempting full coverage (which is rarely feasible, even with small armies of volunteers).
Finally, always remember the hobbyists’ golden rule: it’s not a job, so if it ain’t fun, you’re probably doing it wrong!
There’s an Observation Fields section on observations. That includes things like “Camera trap”, and “Trail Camera observation”. It’s not immediately obvious how to filter on those. (The Camera Traps project doesn’t seem to collect observations algorithmically.)
The field: parameter does work, incidentally — ?field:camera+trap= returns records with that field regardless of value. One trap worth flagging: Explore remembers your last place filter across sessions and silently intersects it with whatever URL you paste, so you get zero results and conclude the syntax is broken.
But the fields are not really where this lives. There is an umbrella project, Camera Trap Projects, aggregating 183,031 observations from a named list of camera trap projects — Camera Traps (Trail-cams) with 134,372, GWMN Texas Nature Trackers 2.0 with 24,311, Cal-Cam with 14,288, and others. It collects by rule from that list, so it is filterable by project_id like any project. Anyone wanting to isolate or exclude camera trap records at scale can already do so across nearly two hundred thousand of them.
That also explains the fields. Of the twenty or so containing “camera”, almost all are deployment metadata rather than markers: Camera Trap Date Deployed, Camera Trap Date Retrieved, Camera height (cm), Camera Trap Placement (with a nice note distinguishing natural food sources from bait), Camera Trap Bait, Is the camera on a game trail? These are not failed attempts at a flag — they describe the deployment, which is the layer above simply saying “this came from a camera.” The two that do read like flags turn out to be a free-text location field (57 records) and a Florida-specific project field (24).
So I joined Camera Traps (Trail-cams) and added a batch. For anyone else arriving here with the same question, the practical notes:
On the question of what counts as one observation, which is where I started: burst frames of a single animal become a single record, but where a group arrives together — a troop of capuchins coming down for fruit one after another inside two minutes — each animal is its own record. A time interval only serves as a presumption when individuals cannot be told apart, which for a nocturnal opossum is most of the time and for a visible group is never. I had been describing this to myself as a thirty-minute rule, and the monkeys made clear that the rule was doing the wrong work.
Where I have landed: the marker problem I was worried about was largely my own ignorance, and the answer is simply to join a project. The open question is still the deployment metadata. Those fields exist and are well designed, but appear little used — and they matter most in a situation like mine, where hundreds of records come from one fixed point. Without deployment dates and placement, a camera trap record tells you a species was present without telling you how hard you looked.
Thanks for pointing me at the fields section. I would not have found any of this otherwise.