Vegetation Patterning Can Both Impede and Trigger Critical Transitions from Savanna to Grassland

TL;DR

This study presents a spatial model of savanna ecosystems showing how vegetation patterns can both prevent and trigger critical transitions between savanna and grassland, revealing new early warning signals.

Contribution

The paper introduces a minimalistic spatial model that uncovers mechanisms of vegetation patterning influencing ecosystem stability and tipping points in savanna environments.

Findings

Vegetation patterns can persist where non-spatial models predict collapse.

Identification of a 'Turing-triggers-tipping' mechanism causing tipping events.

Transient spatial patterns serve as early warning signals for ecosystem transitions.

Abstract

Tree-grass coexistence is a defining feature of savanna ecosystems, which play an important role in supporting biodiversity and human populations worldwide. While recent advances have clarified many of the underlying processes, how these mechanisms interact to shape ecosystem dynamics under environmental stress is not yet understood. Here, we present and analyze a minimalistic spatially extended model of tree-grass dynamics in dry savannas. We incorporate tree facilitation of grasses through shading and grass competing with trees for water, both varying with tree life stage. Our model shows that these mechanisms lead to grass-tree coexistence and bistability between savanna and grassland states. Moreover, the model predicts vegetation patterns consisting of trees and grasses, particularly under harsh environmental conditions, which can persist in situations where a non-spatial version of the model predicts ecosystem collapse from savanna to grassland instead (a phenomenon called ``Turing-evades-tipping''). Additionally, we identify a novel ``Turing-triggers-tipping'' mechanism, where unstable pattern formation drives tipping events that are overlooked when spatial dynamics are not included. These transient patterns act as early warning signals for ecosystem transitions, offering a critical window for intervention. Further theoretical and empirical research is needed to determine when spatial patterns prevent tipping or drive collapse.