Washington, May 27 (ANI): In a new research, scientists have found a formula to uncover the Earth’s past and predict its future.
The novel method, found by a research team from California and Lancaster, involves reconstructing missing data that will shed new light on how and why our climate moved us on from ice ages to warmer periods.
That will be possible as researchers will be able to calculate lost information and put together a more complete picture.
Similarly, they will be able to tackle ecological studies that are currently incomplete or distorted.
Questions like, why do populations of animals like rabbits and foxes fluctuate so dramatically, and which factors most heavily influence population decline and, eventually, lead to extinction, might be answered.
The research may offer 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.
It could potentially uncover new findings on topical scientific issues such as climate change and the extreme population fluctuations in some animal species.
By developing a novel Hamiltonian approach to the problem, using a mathematical algorithm, assuming the dynamics of each system has unknown parameters and that the data are distorted by random fluctuations, the researchers were able to successfully recreate measurements in a study on a vole-mustelid community.
Many small mammalian species have cyclic population dynamics, periodically oscillating between large and small communities, a behavioral phenomenon that has puzzled ecologists for decades.
Reconstructed data on such predator-prey dynamics could now give new insight into why some species suddenly decline.
Climate evolution is subject to similar cyclical variations, which could be uncovered by applying the method to measuring the distribution of isotopes in sediments taken from the ocean floor, potentially giving further insight into the reasons behind climate change.
According to the researchers, “The method will also be applicable quite generally to cases where some state 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. (ANI)