Home » Honeybees and missing data part 3: Ant search optimisation

Honeybees and missing data part 3: Ant search optimisation

by Jack Simpson

Earlier in the year I had to reset the observation hive and sadly that process resulted in the death of a fair few bees who ended up on the ground. Now, I knew that there were large carnivorous bull ants in the area and I completely expected them to clear away the bodies within a few hours. Unexpectedly though, none of the bodies were removed.

After a couple of days, I took a closer look and noticed something interesting – the bull ants were missing, but the tiny ants* in the area had found them! I’ve circled a few of them in the image below.

I thought this was rather interesting: here we had a huge source of food, and yet the bull ants I frequently saw on the ground had remained completely oblivious.

I had a chat with some ant researchers that evening and finally understood why this had occurred: it was due to the different search strategies these ants employ. You see, the smaller ones dedicate their resources to searching the environment extensively, and when they find a food source, they will recruit other ants to take advantage of it.

On the other hand, most of the bull ants will go to a single tree where they know there is a consistent source of food, and only a few individuals will explore the environment for additional sources of food. Then, if they do find a new food source, they lack the ability to recruit other ants to take advantage of it as effectively as the smaller ants.

I find the differences between these strategies absolutely fascinating, and it makes me wonder which is the most effective in the long term and/or in different environments?

Is it better to have more flexibility in your search for resources, and to more effectively adapt to sudden changes? Or is it better to identify a consistent resource and focus your energy on harnessing it as effectively as possible? After all, you never know when another ant will come along and eat your lunch.

I feel as though it’s little observations like these that perfectly illustrate how much we can learn from the complex behaviour and social interactions of insects.

*Tiny ants: scientific term for an ant species that a bee researcher could not identify and forgot to ask the ant researchers for more information.

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Currently fascinated by energy markets and electrical engineering. In another life I was a beekeeper that did a PhD in computational biology writing image analysis software and using machine learning to quantify honeybee behaviour in the hive.

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