I’m sure, when the internet was in its infancy, that nobody thought a major use would be for sharing photos and videos of cats. Cats have covevolved with humans for thousands of years. If we ever needed an example of how much they control that interaction then this flood of cat images would be exhibit A. I don’t see cats taking photos of us and sharing them around.
I’m not judging anyone here. My phone has more than a few photos of the two cats that let us share their hourse. Our cats are called Charles (Charlie) and Ernst (Ernie). Named after Darwin and Mayr, of course, two great evolutionary biologists. Over the years I have taken a bunch of photos of these cats. But here’s the thing, if you were to look at my photos on my phone you would find that photos of Ernie outnumber Charlie by [pops off for a quick count] 15:1.
What does this ratio tell you about cats at our house? It might suggest that there are two cats present. While this is generally correct, there are a couple of other cats that do wander through our property most days (including a nasty white one that tries to eat our cats’ food and fights with them). They don’t get to have photos taken!
The ratio might suggest that Charlie is not present all that often, while Ernie is always about. There is a little truth to this; Ernie is a real-live scaredy cat who almost never leaves the house or our garden; Charlie is a great hunter, explores the wider area, and has made friends with the neighbours, where he spends much of his time. However, Charlie is still present around our house several times a day. So the ratio is not accurate in that regard.
The main reason for this skewed ratio is that Ernie is a classic fat cat. She is cute, loves hanging around known people, and is always offering photo opportunities. Charlie is hard to love. He suffers from a post earthquakes stress disorder, for which we have to medicate him, and really doesn’t like being in our house much. He does not hang around us very much, is not particularly friendly, and offers few photo opportunities.
What we have, then, is a differential observability of individuals. Some individuals are just easier to detect than others. This is a classic problem when it comes to monitoring species. If we have a population that we need to count over time, then we need to have a method that can detect individuals with a similar chance of finding each individual.
Taking photos of cats is not just something that bored people do around their homes. Cats, especially feral ones, have major impacts on species in natural habitats. In New Zealand, cats are found throughout our landscapes. From a management aspect we are always interested in finding out where they are and how many individuals live in an area.
Camera traps are increasingly used for finding and recording species in the wild. We already use them to locate cats but we can always do better. Trail cameras that can be set and left to record movement were originally created for locating deer. As such, they are not optimally designed for detecting smaller, faster species, like cats, stoats and possums.
Maggie Nichols recently completed her PhD at Lincoln University, working with James Ross, Adrian Paterson and Al Glen (Landcare Research). Her research focussed on how we can use trail cameras to better target species of interest to New Zealand wildlife management. One of these species was cats.
If we want to take more, and better, pictures of cats in the wild, how should we set out our cameras? Maggie tested two different methods on farms in the Hawkes Bay. One method was to set the cameras out on a grid pattern, which would cover all of an area and all types of habitat. The second was to place the cameras predominantly in habitats where previous research suggested that cats are more likely to spend time; forest and forest edges rather than open farmland and scrub.
Overall, 96 cameras were deployed, amounting to 2016 nights of recording. Around 150 000 photos were taken. Of these, 92 000 were false triggers (wind-blown vegetation for the most part) and 26 000 were livestock. There were around 23 000 ‘selfies’ of wild species (birds, ship rats, mice, hares, possums, hedgehogs, mustelids, pigs, and goats).
This left around 6000 pictures of cats. Maggie worked her way through this deluge of images and has published her work in the journal Animals. She found that cameras were 10 times more likely to pick up cats in forest and forest edges than in open farmland or scrub. If the goal of a monitoring programme is to locate cats, then placing your cameras in forest habitats around farmland is more likely to find them than randomly placed cameras.
With this and other research on cameras and cats, Maggie has more ideas about how to locate cats. Given their differential observability between individuals and habitats, it might be useful to place cameras in pairs or clusters to make sure we are not missing any cats that pass close to a camera. Orientating cameras so that they face down at the ground rather than out to the horizon looks promising for identifying individuals by their markings or other features. This would allow us to know how many cats are in an area and how much they move around.
Next time you are taking a picture of your cat, stop and consider what the image can tell you about their behaviour and think about the science behind it.