Scientists have evolved a formula which will unravel how and why our climate moved us on from ice ages to warmer periods.
Similarly, researchers will be able to tackle ecological studies that are currently incomplete or distorted. Why do populations of animals like rabbits and foxes fluctuate so dramatically? Which factors most heavily influence population decline and, eventually, lead to extinction?
The approach offers a solution to the problem of reconstructing missing or lost information in studies of dynamical systems such as the Earth's climate or animal populations.
By developing a novel Hamiltonian approach to the problem, using an algorithm, researchers from California and Lancaster universities were able to successfully recreate measurements in a study on a vole-mustelid (fur-bearing carnivorous mammal) community.
Many small mammalian species have cyclic population dynamics, oscillating between large and small communities, a behavioural phenomenon which has puzzled ecologists for decades.
Reconstructed data on such predator-prey dynamics could now give new insight into why some species suddenly decline.
As the researchers write: "The method will also be applicable quite generally to cases where some variables could not be recorded."
These could include, not only climate change and ecology, but also contexts such as populations at risk from epidemics and rocket motors for new space crew exploration vehicles.
These findings are slated for publication in the June issue of New Journal of Physics.