Master Thesis Defense by Carl Ivarsen Askehave

Title: Tipping points and early warning signals in complex ecosystem models

Abstract:
Several large ecosystems face irreversible, abrupt transitions to different states. Drylands in semiarid climates may experience desertification as water supplies decrease or wildfires intensify. Similarly, large rainforests could transition to savannahs. These shifts are driven by positive feedback loops that become dominant at tipping points (TPs), mathematically described as saddle-node bifurcations, leading to rapid, system-wide changes. Critical slowing down (CSD) can predict TPs by monitoring increased variability in observables, acting as early-warning signals (EWS). However, spatio-temporal effects, such as spatial heterogeneity and scale-dependent feedbacks are often not included in the modeling of TPs. This project aims to understand how ecosystem TPs change with increasing complexity of the positive feedbacks inherent in local-scale ecosystem models. To this end, different stable vegetation configurations in the models are found numerically, and the bifurcations of these patterns are determined as control parameters (e.g., mean annual rainfall) vary. It is investigated what happens at the TP of vegetation collapse, i.e., which variables or observables change most in terms of their mean and variability, and this may guide the choice of observables to use in EWS for similar systems. The model simulations performed in this project will be used to constrain under which circumstances abrupt, system-wide ecosystem collapse can be expected, and to assess whether a collapse may be predicted from real-world-observations.

Supervisors: Peter Ditlevsen, Johannes Jakob Lohmann
Censor: Jens Olaf Pepke Pedersen