Ingrid A. van de Leemput

This paper compares multivariate and univariate resilience indicators for early warning of West Nile virus outbreaks, finding multivariate indicators perform better in data-poor scenarios.

This study examines how temperature affects seagrass recovery across the Western North Atlantic, finding that higher temperatures generally enhance recovery, while nutrient and herbivore interactions reduce it.

This paper compares methods for detecting resilience changes in systems, showing that burst sampling outperforms continuous monitoring with the same data points, suggesting it can improve early warning signals for critical transitions.

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.