Babak M. S. Arani

This paper introduces Euler and Hermite reconstruction methods to estimate Langevin systems from time series data, showing their effectiveness across simulated and real ecological and climate datasets.

This paper introduces an improved potential analysis method to better handle ecological data limitations and enhance predictions of ecosystem dynamics and resilience.

The paper shows that stochastic regimes can obscure attractors in data, and that reconstruction algorithms can reveal them by analyzing the relationship between noise and system equilibria.