Aperiodic clustered and periodic hexagonal vegetation spot arrays explained by inhomogeneous environments and climate trends in arid ecosystems

Abstract

Due to climate change, overgrazing, and deforestation, arid ecosystems are vulnerable to desertification and land degradation. As aridity increases, vegetation cover loses spatial homogeneity and self-organizes into heterogeneous vegetation patterns, a step before a catastrophic shift to bare soil. Several studies suggest that environmental inhomogeneities in time or space are crucial to understand these phenomena. Using a unified mathematical model and incorporating environmental inhomogeneities in space, we show how two branches of vegetation patterns create a hysteresis loop as the mortality level changes. In an increasing mortality scenario, one observes an equilibrium branch of high vegetation biomass that forms self-organized hexagonal-like patterns. However, when the mortality trend is reversed, one observes a branch with low biomass and no periodicity, where vegetation spots form disordered clusters instead of a hexagonal lattice. This behavior is supported by remote sensing and field observations and can be linked to climate change in arid ecosystems.

v1 was split into two different works. This version matches the published theory and simulation part of our work. A new entry will be created for the extended data analysis and applications

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