  The Jacobian matrix of a dynamical system describes its response to
perturbations. Conversely one can estimate the Jacobian matrix by carefully
monitoring how the system responds to environmental noise. Here we present a
closed form analytical solution for the calculation of a system's Jacobian from
a timeseries. Being able to access a system's Jacobian enables us to perform a
broad range of mathematical analyses by which deeper insights into the system
can be gained. Here we consider in particular the computation of the leading
Jacobian eigenvalue as an early warning signal for critical transition. To
illustrate this approach we apply it to ecological meta-foodweb models, which
are strongly nonlinear dynamical multi-layer networks. Our analysis shows that
accurate results can be obtained, although the data demand of the method is
still high.
