Spatio-temporal stochastic resonance induces patterns in wetland vegetation dynamics

TL;DR

This paper demonstrates how spatio-temporal stochastic resonance involving noise, periodic water fluctuations, and spatial coupling can induce stable, patterned vegetation dynamics in wetlands, revealing complex ecosystem behaviors.

Contribution

It introduces a simple model showing how combined stochastic and periodic effects lead to emergent spatial patterns in wetland vegetation.

Findings

Spatio-temporal stochastic resonance can generate ordered vegetation patterns.

Patterns exhibit spatial and temporal coherence and are statistically steady.

The model highlights the role of noise, periodic water fluctuations, and spatial coupling in ecosystem dynamics.

Abstract

Water availability is a major environmental driver affecting riparian and wetland vegetation. The interaction between water table fluctuations and vegetation in a stochastic environment contributes to the complexity of the dynamics of these ecosystems. We investigate the possible emergence of spatial patterns induced by spatio-temporal stochastic resonance in a simple model of groundwater-dependent ecosystems. These spatio-temporal dynamics are driven by the combined effect of three components: (i) an additive white Gaussian noise, accounting for external random disturbances such as fires or fluctuations in rain water availability, (ii) a weak periodic modulation in time, describing hydrological drivers such as seasonal fluctuations of water table depth, and (iii) a spatial coupling term, which takes into account the ability of vegetation to spread and colonize other parts of the landscape. A suitable cooperation between these three terms is able to give rise to ordered structures which show spatial and temporal coherence, and are statistically steady in time.