Local properties of patterned vegetation: quantifying endogenous and exogenous effects

TL;DR

This study introduces a Fourier-based method to analyze local vegetation patterns in drylands, revealing how terrain and water dynamics influence pattern coherence and variability.

Contribution

The paper develops a novel Fourier technique for local pattern analysis and links pattern properties to soil and topography, advancing understanding of dryland vegetation dynamics.

Findings

Local pattern wavelength and orientation are coherent but vary with terrain features.

Soil depth and topography correlate with pattern coherence and wavelength.

Water accumulation influences changes in vegetation pattern properties.

Abstract

Dryland ecosystems commonly exhibit periodic bands of vegetation, thought to form due to competition between individual plants for heterogeneously distributed water. In this paper, we develop a Fourier method for locally identifying the pattern wavenumber and orientation, and apply it to aerial images from a region of vegetation patterning near Fort Stockton, Texas. We find that the local pattern wavelength and orientation are typically coherent, but exhibit both rapid and gradual variation driven by changes in hillslope gradient and orientation, the potential for water accumulation, or soil type. Endogenous pattern dynamics, when simulated for spatially homogeneous topographic and vegetation conditions, predict pattern properties that are much less variable than the orientation and wavelength observed in natural systems. Our local pattern analysis, combined with ancillary datasets describing soil and topographic variation, highlights a largely unexplored correlation between soil depth, pattern coherence, vegetation cover and pattern wavelength. It also, surprisingly, suggests that downslope accumulation of water may play a role in changing vegetation pattern properties.