What-Where-When-Who-Why-How: make sure you do them all
The Why and How are often missing from casual nature watching observations, and museum specimen collections, but they’re just as important as What-Where-When-Who.
written Feb 26, 2019 • by jonsullivan • Category: Wild Counting
Earlier this week, to my great surprise, I saw a kōtuku flying over a suburban neighbourhood park in southwestern Ōtautahi-Christchurch, New Zealand. That’s very unusual—I’ve never seen one before in this suburb—and that makes it an observation worth sharing.
If I shared that observation by itself, it would be another
What-Where-When-Who observation: “Today I saw a kōtuku here!” Nature sharing sites like iNaturalist are filled with observations like this. Mine would tell everyone that there was a kōtuku passing through this part of Ōtautahi on that day. However, if anything, its coordinate on the map would add unwanted noise to calculations of kōtuku distribution and habitat use. Turning
What-Where-When-Who observations into robust population maps and trends is very difficult.
That’s all because
What-Where-When-Who does not make it clear exactly how unusual, or common, each sighting was. I could add some text to the description, like “this is the first time I’ve seen a kōtuku here”. However, that could easily go unnoticed by researchers analysing thousands of kōtuku observations. More importantly, it doesn’t say exactly how often, when, and how hard I’ve looked at this site for kōtuku. This is all because the
How are missing.
How to the
What-Where-When-Who, I can put my observation into proper context. That allows it to be used to calculate robust patterns and trends. It lets people in the future survey this site and connect their observations to mine to assess change.
How are the keys to turning casual nature watching into wild counts.
Why is why was I there when I saw the kōtuku, including which species (if any) I had predetermined, before I arrived, that I would record. In this case, my
Why was that I was out for my weekly wild counting run, and on this run I predetermine to observe all birds, butterflies, wild mammals, plus an assortment of plants and fungi.
Why lets researchers convert my observations into a probability of observing kōtuku at this site. They could use all the other runs I’ve done through this site, when I was looking for all birds and didn’t see a kōtuku. That would reveal exactly how unusual my observation was.
How is my survey method, in this case a running survey with distance sampling, where every bird needs to be first heard with unaided human ear or seen with unaided human eye (although I carry a monocular to confirm IDs of birds I see). My iPhone makes a GPS track of my route which contains my speed. I use a simple form of distance sampling where I count in distance bands away from me, from close (<5 m) to distant (>320 m).
How can let others repeat all, or part, of my surveys in the future to uncover trends. With a well-described
How, observations can be used to estimate my “detection probability” for the species at the site. That’s the probability of detecting a species if it was there. Distance sampling can do this because the probability of detecting a species declines predictably with distance.
So, when done right, the
Why tells us the probability of me observing kōtuku at this site, and the
How can estimate how often I am likely to have overlooked a kōtuku at the site. When combined together, over lots of surveys,
How can give researchers estimates of the density of kōtuku in different areas and at different times. That’s exactly what’s needed for calculating robust patterns and trends for species.
The difference between
What-Where-When-Who nature watching and
What-Where-When-Who-Why-How wild counts is night and day. It’s the consistently recorded
How that make wild counts much more useful than nature watching.
Most modern nature watching observations are analogous to taxonomic collections, but with photos or audio recordings replacing specimens. A good taxonomic observation accurately and precisely records a
What-Where-When-Who of one moment in nature. There’s sometimes also a
How (for example, a moth was caught at a light trap) but very rarely a
Some nature watching observations, like some taxonomic specimens, can be incredibly valuable, such as the first record of a species in a new area. However, without the
How, it’s very difficult to turn masses of such observations into reliable patterns and trends to reveal bigger stories. Doing so requires making lots of tricky assumptions about the
Why behaviours and movements of observers.
Wild counts should be more than just nature watching. By adding
What-Where-When-Who, our wild counts are useful for making discoveries (like “that’s the first time that species has been recorded here”) and for monitoring changes.
Why to nature watching is just as much fun, and just as easy, as leaving them out. It just takes a bit of care and practise at first to get into the habit. In my case, it’s the difference between “Today I saw a kōtuku here!” and “Today I went for my weekly run, looking for all birds, and I saw a kōtuku here!”. If you’re keen on nature watching, have a think about how to turn some of your observations into wild counts.
What-Where-When-Who-Why-How: the essentials of wild counting.
You can note the
Who-Why-How just once, at the start of a trip, turn on your GPS, and then focus on making lots of
What-Where-When observations along the way.
||What species did you find and how many individuals did you see at this spot at this moment? Be sure to include a question mark if you're not 100% certain of your ID. In some cases, this will be backed up by a photo, audio recording, or collected specimen, but those aren't essential once you've established a good track record of being able to reliably identify a species. You can make lots of
||This is the coordinate of exactly where you counted your species. If you've got a GPS track running on your smart phone or GPS unit, you only need to record the exact time of each observation and you can extract the exact location of each observation later, from your GPS track. That's the fastest thing to do if you're making lots of observations. Otherwise, drop a pin in your favourite GPS app and copy the coordinates.|
||This is when you see or hear a species that you count. Make sure that your date and time are in unambiguous formats, like 9:30 PM or 21:30, not just 9:30, and 10 Dec. 2019 or Dec. 10 2019 and not 10/12/19 (which means different things in different parts of the world). The international date format is year-month-day, e.g., 2019-12-10. Add the time zone if that's convenient, although researchers can also get that from your
||That's you, of course, but if you're helped by other people, then name them too, as you're likely to find more when you're part of a team. If they’d rather be anonymous in your shared data, but they were helping you with your counts, then it’s much better to label them with codes unique in your counts (for example,
||Decide before you start your survey exactly what you're looking for, and when you’ll stop counting. Perhaps you're just looking for one species, or perhaps you're looking for many. Regardless, the important thing is to decide before you start. It's also important to decide in advance when you'll stop. Always searching for five minutes is quite different, and much more consistent data, than searching until you find what you're looking for. It’s best for your stop time to be completely set in advance, and not affected by how much you count.|
||Describe how you search for the species you're looking for. This could be something simple like manual searching, or something more complicated involving gadgets. Make sure that you describe what you do consistently across your trips and in enough detail that others can repeat it. Record your start and stop time and make a GPS track of exactly where you search. It's useful to also describe other conditions that might influence your chances of finding your species, like the weather and the visibility and the background noise.|