Sorry if there is already a post like this one, but I’ve started a project that focuses on recording occurrences of reptile predation on other animals in Australia and was wondering if any of the more experienced Inat users have any tips or recommendations on how to more effectively look through the massive list of observations for such specific occurrences.
The best I’ve been able to figure was sorting by ‘Favourites’ as predation behaviour is more likely to be favourited than regular behaviour, this along with just running across observations whilst ID’ing has been the main ways I’ve found observations from my project, neither of which are especially effective.
I also plan on making a similar project but for inter and intra-specific interactions with monitor lizards, so effective search/filter methods are something I would greatly appreciate.
Have you tried putting “prey”, “eat”, “ate”, etc. in the Description filter when searching for Australian reptiles? Doing “prey” got me many reptiles as prey, but also this observation and a few others where the note was talking about the reptile’s prey. Based on that observation, there’s also a Snake Predation Records project. As fmiudo mentioned, there are also various Observation Fields people use for predation.
I’m no pro at using iNaturalist, but I would probably go about this by first searching for observation fields (e.g. eating, eaten by) that have been filled out.
Here is a link to all the reptile records in Australia with the ‘eating’ field filled out. There are more records here than are in your project, so I’m guessing you’ll be able to add some to your project.
Finding observations that haven’t had the observation fields filled out will be more difficult, but I would personally go about it using the photo browser. You can scroll non-stop and see each photo better than if you were to use the Explore or Identify tabs.
You can’t save your place in the photo browser, so I would break it down into smaller taxa and locations within Australia. For example, you might start with freshwater crocodiles and scroll through Queensland first, then Northern Territories, then Western Australia. Saltwater crocodiles have more records, so maybe you break it down into even smaller locations (it looks like the Australian states break down into ‘shires’?), or maybe you can break it down in some other way.
If you do use the Identify tab, it has the added benefit that you can mark observations as reviewed, which is a way of saying ‘I’ve looked at this, don’t show it to me again.’ Then you don’t risk looking through the same observations over and over again.
Something that can help is to set up a project for this behavior (or see if there already is one) and then try to make sure lots of Australian iNatters, especially herpers, know about it.
If you can pick out annotations which would not apply, you can filter those out - annotations aren’t applied perfectly, but it does at least reduce the stuff to look through. You could also pick annotations that do apply and search those after you’ve gone through the observation fielded ones.
Since these are probably more right place/right time observations than something people can systematically go out looking for, I suspect identifiers and people who run similar projects would probably be your best bet.
I’d recommend messaging people who have a lot of Australian herp observations. (They may already have some observations they can point you to.) Also comment on some observations, especially where you can see the behavior you want and ask about getting more. You might want to point the observers to the existing project Who Eats Whom or set up your own.
If you wanted to, I guess you could do a journal post where you link to the ongoing list. The advantage is that if they select a specific observation field (like the one you’re using… “18293 - reptil prey species”), they can filter by either the reptile or prey species by clicking the taxon in the table. The most common obs fields used are 18293, 3134, and 13.
The table encourages the normalization of obs field data because you can’t and/or the obs fields together. If you normalized the Australia data so that each observation used one obs field, the data in the table wouldn’t need to be “merged” and the observers in the project could more easily filter it. The problem is… if you add a single obs field to every applicable obs that doesn’t already use it, it spams a bunch of users.
I’m not really sure what the “best practices” should be.
Also… some observers don’t allow obs fields to be added to their obs by others.