Once you've had a tangle with the housing market, it's easy to understand why fiddler crabs are so determined to defend their real estate. Watching the tiny creatures rush home when an intruder threatens left Jochen Zeil and Jan Hemmi in no doubt that the crustacean's home is its castle. But how the crab saw the impending threat, and quickly decided on a course of action, wasn't clear. Travelling to the crab's home beaches in Queensland, Australia, Hemmi set up a bird's eye vigil, watching the crab's responses as a dummy crab threatened. But thinking from the defending crabs perspective, Hemmi couldn't find a defence triggering pattern in the dummy's movements, until he switched to a different point of view; the burrow's. No matter where the defender was relative to its home, as soon as an intruder came too close to the entrance the owner came scuttling home, even if the burrow was out of sight!
`Fiddler crabs are fantastic animals' says Hemmi; `with a small camera above you see everything they do in a day out'. Snatching the brief periods between high tides, Hemmi rigged up a system of strings and pulleys to tow a crab dummy past a burrow's entrance as he filmed the home owner's reaction to the threat. The crabs were convinced enough to retreat to their burrows every time the dummy rolled past; some even abandon their homes after a prolonged series of dummy threats. But once Hemmi had gathered over 40 hours of defensive film footage, the real work started; looking for a pattern to the animal's behaviour.
At first Hemmi made little headway. He tried constructing spatial histograms of the dummy crab's movements, without success. But the break came when he thought of switching reference frames. Instead of thinking from the camera's view, he began thinking of the dummy's trajectory from the perspective of the crab and burrow. By drawing a vector between the crab and its burrow, and superimposing many dummy paths on the calculated vector, Hemmi realised that the crabs weren't reacting to their attacker's proximity; it was the attacker's distance from the burrow that triggered a defensive run home(p. 3935)! Once the attacker came close to the burrow, the defender came running. And Hemmi and Zeil were amazed that the homeowners reacted even when their burrows were out of sight! Somehow they were working out the distance between the attacker and the burrow, but how? The tiny crabs were either calculating the distance from first principles, or they'd figured out another way to judge the aggressor's approach.
Hemmi quickly ruled out the arithmetic alternative. If the crabs were calculating the distance between the intruder and burrow, they'd need to know their distance to both objects, before they could complete the triangle and measure the intruders proximity to the burrow. Hemmi realised that the crabs would also have to measure an angle as well as being quadric equation solving geniuses; too tall an order for a 2 cm long crab.
But Hemmi and Zeil knew enough about the crab's simple visual system to plot a view of the world from a crab's eye height. They plotted how the beachscape looked when the crab was 10, 20 and 30 cm from the burrow(p. 3951). They realised that if the crab was to defend its burrow, it need only know its distance from home, call up the map that represented its view, and see where the intruder's position lay on the map. If the intruder was in the map's safe zone, the crab could rest easy, but as soon as the intruder stepped too close and into a danger zone, the threatened burrow owner could leap into action and protect its patch.
Hemmi says `this is a wonderful example of an animal dealing with complexity in its environment... to achieve a task'. He explains that the crabs always keep a tally of their distance from the burrow, so the only extra information that they need to solve the mind boggling 3D problem is a set of neurons with preprogrammed maps to solve their home defence problem.