What-Where-When-Who-Why-How: make sure you do them all

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 Why and How are missing.

By adding Why and 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. Why and How are the keys to turning casual nature watching into wild counts.

The 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.

Knowing the 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.

The 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).

The 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, Why and 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 Why and 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 Why.

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 Why and 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 How and Why behaviours and movements of observers.

Wild counts should be more than just nature watching. By adding Why and How to 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.

Adding the How and 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.