I’ve written about the methods that we use in behavioural ecology, and the method that I use the most is definitely modeling. To be more precise, I do a lot of computer simulation work on the evolution of behaviour (my focus is on evolutionary algorithms and individual-based models). I do some formal mathematical modeling as well, primarily in game theory, but the bulk of my research is computational. I admit it: I’m a computer geek, and I always have been. I love writing software, I love tinkering with code and hardware, and my natural approach to biological questions has always been to throw processor cycles at them.
Which leaves me wondering: what do we call computational studies of behavioural ecology?
The obvious answer, computational biology, is – I think – wrong. At least, as it is currently defined, computational biology seems to be heavily focused on questions at the level of the cell or below. If you look at the Wikipedia entry on computational biology, you’ll see that the examples given are all about cells, molecular biology, genomics, and so on. Bioinformatics, computational genomics, “computational biomodeling” (not sure what that is, to be honest), systems biology, etc. are all examples of labels under the heading of computational biology, and none of them apply to the kind of work I do. It’s natural that a lot of attention would be focused on this level of inquiry – people doing exciting work in genomics, cell biology, and proteomics are drowning in data and need computers to help them climb out of the well. But I spend my time at the level of the individual and the evolution of their behavior, which doesn’t give me a lot to talk about with the computational biology people.
At the other end of the scale is the relatively new field of computational ecology. If you forced me to chose right now, I would probably throw in with this camp, but it’s still a bit of an uneasy fit. Computational ecology focuses on global population-level questions, and big ecosystems with many layers of complexity. This is a fascinating area of work, but just like behavioural ecology differs from classical ethology / ecology in focusing on the individual, so too does the work I do focus on the evolution of mechanisms and behaviour at the level of the individual. A typical question that I’m working on right now is the evolution of learning mechanisms for social foraging – how do animals learn to use the best strategy when foraging in a group, and what is the form of the mechanisms which allow them to do that?
And in the end, I’m left wondering where I fit. There are others like me, of course; for example, I’ve always admired the work of Dr. Graeme Ruxton, as well as the Laland group, both of which have done work in the same vein (this is by no means an exhaustive list, of either the people whose work I admire or who do work in the same area). With the increasing specialization of scientists into subfields of subfields of major fields, I’m hesitant to invent a new term for myself and others like me, but maybe it’s time.
So: computational behavioural ecology, anyone?
(Photo credit: Network Osaka)