Studying complex systems like ecosystems can get messy,
especially when trying to predict how they interact with other big unknowns
like climate change.
In a new paper published this week (May 20) in the
Proceedings of the National Academy of Sciences, researchers from the University
of Wisconsin-Madison and elsewhere validate a fundamental assumption at the
very heart of a popular way to predict relationships between complex variables.
To model how climate changes may impact biodiversity,
researchers like Jessica Blois and John W. (Jack) Williams routinely use an
approach called "space-for-time substitution." The idea behind this
method is to use the information in current geographic distributions of species
to build a model that can predict climate-driven ecological changes in the past
or future. But does it really work?