When you count the fish, the fish may be counting you…

Once Upon A Time, in a land far, far away from where I’m writing this, I worked for a non-profit science education research corporation called TERC. I did a number of different kinds of work there, but my favorite was designing lesson plans and activities to help people learn about ecology and climate science. One of teams I was on did a lot of outreach to schools, museums, nature centers, aquaria, and other organizations that dealt with science education in New England, with the goal of building connections between schools and “informal” educational institutions, so that kids could do actual research activities as part of their science education.

Climate change ecology is a field that spends a lot of time on phenology – the study of seasonal behavioral patterns. The first lessons in our Climate Lab project involved spring leaf-out, and bird migration, for example, and some of the first research I dug up for a list of recorded changes due to climate change was fish moving north earlier in the season, because the water was getting too warm. It makes sense, right? With the temperature rising, and the weather getting more unpredictable, plants and animals have been getting mixed signals from their environment, and it’s been throwing everything into chaos for at least a couple decades now. Insects and plants come out early because it’s warmer. That’s fine for the insects, but it’s terrible for the plants and the birds. A lot of migratory birds rely on things like day length or some evolved internal clock or sense of Earth’s orbit. That means that they can’t change their timing in response to changes in weather – climate change doesn’t affect that.

So the birds arrive late, because the bugs were out early, and their offspring either starve, or don’t get as good a start on life. More than that, the annual horde of caterpillars are no longer kept in check by birds, so they do a lot more damage to the plants they eat, which in turn makes them less resilient.

And that’s just one set of relationships. It doesn’t touch on how mammals fit in, the effects on things like pollination, or how the damage to the migratory bird population affects the ecosystems in South or Central America where they spend their winters. As I studied this stuff, I got a distinct feeling that although I couldn’t see it, the entire surface of the planet was seething around us, like the ripples on the surface of a pot of water just about to boil. Plants and animals are evolving – changing their shapes and sizes in response to their changing environment. The birds I mentioned before are changing their migratory timing, but they’re doing it the hard way; the individuals who migrate too late often can’t keep their young alive, and those that migrate earlier do a little better. Generation by generation, death by death, everything around us is changing; but it’s not changing fast enough.

If we ever get our act together, politically, and start trying to actually clean up our mess, we’re going to want to know what’s been happening in the ecosystems around us. That will give us the tools we need to help shore up their weaknesses, and help rebuild the ecosystems on which we depend. That’s why it’s essential that the sciences continue to be a priority as we deal with this chaotic new world, and why I was so proud to be part of a project that was teaching people how to participate in that research, even without any actual training in science.

The activities I helped design were often based on the specialties and resources of the nature center in question, be it fish or fowl, and at the tail end of my time at TERC, I started working on materials connected to the Mystic River Watershed Association (MRWA. In particular, we were focused on fish migration. Salmon are probably the most famous (and in my opinion best-tasting) anadromous fish, but the waters of the world are teeming with fish that live most of their lives in the ocean, but swim up streams and rivers to breed. Probably the second most famous, at least in the Boston area where I used to live, is the Alewife. The Alewife is an anadromous herring that historically ran in streams along the northern Atlantic coast of North America. It’s the name of the northernmost station on the MBTA’s Red Line, and the name of a nearby brook. Alewife brook used to be filled with the fish every year, but in living memory, it has been a polluted roadside canal inhabited by algae and invasive carp.

That said, there have been conservation efforts along the coast, in contrast to the control efforts further west, where canals and shipping have turned them into an invasive species. The MRWA is responsible for one of the conservation successes, and they oversee a fish ladder to allow Alewife and their cousin species the blueback herring to get over a dam and into the Mystic Lakes, where they spawn. In this case, “oversee” is literal, as they’ve got a camera to record the fish during their seasonal runs, to help track the population.

The problem is, the only way to be sure of their numbers is to literally count them. It’s a monumental task, and one that’s ripe for counting errors. They’ve found a brilliant solution, and it gets back to the kinds of educational activities I mentioned at the beginning. There’s a website where anyone in the world can look at sections of video, count how many fish they see, and enter that number. The video presented is random, and your count is considered along with everyone else who entered a count for that same video. That means that if I count a leaf as a fish, your more accurate count basically cancels out my error. When you have a dozen different people looking at each video, the odds are pretty good that an accurate consensus will emerge. There’s no need for a supercomputer or for someone to spend countless hours watching blurry fish go by a window, and trying to stay focused enough to get an accurate count.

Some poor intern, or maybe a graduate student, working late into the night for far too little money, running on cheap coffee and food from the vending machine down the hall. Everyone else is in bed by now, but he has to count the endless stream of fish, and every time he loses track, he has to restart the video, until time seems to blur together and his Sisyphean task becomes a surreal daydream. And now the fish aren’t just swimming by. They’re looking at him through the window. No. It’s a video. He’s in the computer lab but… They see him. He’s certain of it. Are they- could they be counting him?

The image shows Ancient Aliens producer Giorgio Tsoukalos saying,

This brings us to the reason I wrote this post.

Suppose there are some coins on the table in front of you. If the number is small, you can tell right away exactly how many there are. You don’t even have to count them – a single glance is enough. Cichlids and stingrays are astonishingly similar to us in this respect: they can detect small quantities precisely – and presumably without counting. For example, they can be trained to reliably distinguish quantities of three from quantities of four.

This fact has been known for some time. However, the research group led by Prof. Dr. Vera Schluessel from the Institute of Zoology at the University of Bonn has now shown that both species can even calculate. “We trained the animals to perform simple additions and subtractions,” Schluessel explains. “In doing so, they had to increase or decrease an initial value by one.”

Blue means “add one,” yellow means “subtract one”

But how do you ask a cichlid for the result of “2+1” or “5-1”? The researchers used a method that other research groups had already successfully used to test the mathematical abilities of bees: They showed the fish a collection of geometric shapes – for example, four squares. If these objects were colored blue, this meant “add one” for the following discrimination. Yellow, on the other hand, meant “subtract one.”

After showing the original stimulus (e.g. four squares), the animals were shown two new pictures – one with five and one with three squares. If they swam to the correct picture (i.e. to the five squares in the “blue” arithmetic task), they were rewarded with food. If they gave the wrong answer, they went away empty-handed. Over time, they learned to associate the blue color with an increase of one in the amount shown at the beginning, and the yellow number with a decrease.

But can the fish apply this knowledge to new tasks? Had they actually internalized the mathematical rule behind the colors? “To check this, we deliberately omitted some calculations during training,” Schluessel explains. “Namely, 3+1 and 3-1. After the learning phase, the animals got to see these two tasks for the first time. But even in those tests, they significantly often chose the correct answer.” This was true even when they had to decide between choosing four or five objects after being shown a blue 3 – that is, two outcomes that were both greater than the initial value. In this case, the fish chose four over five, indicating they had not learned the rule ‘chose the largest (or smallest) amount presented’ but the rule ‘always add or subtract one’.

Computing without a cerebral cortex

This achievement surprised the researchers themselves – especially since the tasks were even more difficult in reality than just described. The fish were not shown objects of the same shape (e.g. four squares), but a combination of different shapes. A “four”, for example, could be represented by a small and a larger circle, a square and a triangle, whereas in another calculation it could be represented by three triangles of different sizes and a square.

“So the animals had to recognize the number of objects depicted and at the same time infer the calculation rule from their color,” Schluessel says. “They had to keep both in working memory when the original picture was exchanged for the two result pictures. And they had to decide on the correct result afterwards. Overall, it’s a feat that requires complex thinking skills.”

To some it may be surprising because fish don’t have a neocortex – the part of the brain also known as the “cerebral cortex” that’s responsible for complex cognitive tasks in mammals. Moreover, neither species of fish is known to require particularly good numerical abilities in the wild. Other species might pay attention to the strip count of their sexual partners or the amount of eggs in their clutches. “However, this is not known from stingrays and cichlids,” emphasizes the zoology professor at the University of Bonn.

She also sees the result of the experiments as confirmation that humans tend to underestimate other species – especially those that do not belong to our immediate family or mammals in general. Moreover, fish are not particularly cute and do not have cuddly fur or plumage. “Accordingly, they are quite far down in our favor – and of little concern when dying in the brutal practices of the commercial fishing industry”, says Vera Schluessel.

I’m afraid it’s true; the whole science education and alewife thing was just a red herring.

Aside from all the other ways this kind of research is useful and interesting, I think it makes a good reminder of how evolution actually works. Contrary to popular mythology, no species on this planet is more or less “evolved” than any other. We’ve all been here the same amount of time, and we all evolved as conditions guided us. When being able to do just a little math helps something survive and reproduce, then that ability will stick around. It’s the same as light-sensitive cells evolving into eyes. Natural selection isn’t random, but the fact that we ended up where we are as a species is random.

As sapient animals, we’re in this weird position where we survive by killing and consuming other life forms, but we can also recognize that those life forms are literally our relatives. I have yet to square this feeling with the fact that I’m not a vegetarian, but when I learn something like this about a fellow animal, I just want to cheer on my “cousin” for being smarter than we realized.

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  1. StevoR says

    ..phenology – the study of seasonal behavioral patterns.

    I’d never heard that term before. Something new learnt today. Thanks.

    Excellent blog post here too.

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