In recent years, a small revolution has occurred in the study of animal foraging patterns. Various new ways have emerged to track and record the movement of animals over relatively long periods and computer scientists have developed models that do a good job of reproducing this behaviour for many living things.

The curious thing is that these models are largely based on random walks. In these simulations, an entity’s next move is almost entirely independent of all its previous moves. Memory is of little or no significance to these creatures.

These models work well for inanimate processes such as Brownian motion and the movement of bank notes but also capture the behaviour of zooplankton, marine predators and even spider monkeys.

That’s surprising because many animals have developed good memories that allow them to perform sophisticated cost-benefit analyses: should I revisit the fruit tree I raided last week or spend time and energy looking for a new one?

It’s easy to imagine that a good memory would confer significant benefits to a foraging animal.

But it’s not quite so straightforward, say Denis Boyer at Universite Paul Sabatier in France and Peter Walsh at the Universidad Nacional Autonoma de Mexico in Mexico.

These guys have created one of the first computer models to take into account a creature’s ability to remember the locations of past foraging successes and revisit them.

Their model shows that in a changing environment, revisiting old haunts on a regular basis is not the best strategy for a forager.

It turns out instead that a better approach strategy is to inject an element of randomness into a regular foraging pattern. This improves foraging efficiency by a factor of up to 7, say Boyer and Walsh.

Clearly, creatures of habit are not as successful as their opportunistic cousins.

That makes sense. If you rely on that same set of fruit trees for sustenance, then you are in trouble if these trees die or are stripped by rivals. So the constant search for new sources food pays off, even if it consumes large amounts of resources. “The model forager typically spends half of its traveling time revisiting previous places in an orderly way, an activity which is reminiscent of the travel routes used by real animals, ” say Boyer and Walsh.

They conclude that memory is useful because it allows foragers to find food without the effort of searching. “But excessive memory use prevents the forager from updating its knowledge in rapidly changing environments,” they say.

So too much reliance on memory is bad.

That throws some interesting light on the forces that must govern the evolution of memory and intelligence. Take as an example the question: if the ability to remember is such a good thing, why hasn’t evolution given us photographic memories? The answer according to Boyer and Walsh’s model is because we’d starve when the local supermarket went out of business.

The next question, of course, is what are the best cognitive strategies for exploiting an imperfect memory. Let’s hope we can remember it long enough to find out.

Ref: arxiv.org/abs/1006.0079: Modeling The Mobility Of Living Organisms In Heterogeneous Landscapes: Does Memory Improve Foraging Success?