Ecosystems are a chaotic battle royale, with predators and prey, plants and animals, competitors and allies all fighting it out to eat or be eaten. But the food webs scientists typically put together are deceptively tidy diagrams, with simple arrows connecting diners to their natural food options. Ecologists readily admit that a true representation of an ecosystem's network would be multi-dimensional, simultaneously taking into account multiple traits for each species involved. But just how many dimensions would such a model need to accurately depict the complexity of a large ecosystem? 10? 100? 1000?
In a new paper published this week in Ecology Letters, a team led by scientists at the Computation Institute and University of Chicago calculate that number – and find that it is surprisingly low. Using data collected by their co-authors on 200 different food webs, ranging from the Caribbean reef to New Zealand grasslands to an Arctic Ocean inlet, Anna Eklöf, Stefano Allesina and colleagues looked for the minimum number of dimensions and traits needed to accurately describe a food network. The findings may save ecologists time and effort in revealing the structure underlying an ecosystem, and also help scientists build computational models that can make predictions about an ecosystem's future.
"To collect this kind of data takes ages to do," said Eklöf. "If we can find some common rules about these networks, then we can apply them to larger networks. We can also learn about the function of networks, and what happens to networks when we disturb them in different ways."