Resolving soil and surface water flux as drivers of pattern formation in Turing models of dryland vegetation: A unified approach

PHYSICA D-NONLINEAR PHENOMENA

卷:414

Article

Siero, Eric^1,2 

[1] Carl von Ossietzky Univ Oldenburg, Inst Math, D-26111 Oldenburg, Germany

[2] Univ Utrecht, Dept Earth Sci, NL-3584 CB Utrecht, Netherlands

关键词: Reaction-diffusion;    Desertification;    Self-organization;    Model comparison;    Model reduction;    Minimal model;   

DOI  :  10.1016/j.physd.2020.132695

来源: Elsevier

【 摘 要 】

Over the past two decades, multi-component dryland vegetation models have been successful in qualitatively reproducing the spatial vegetation patterns widely observed in nature. In the two-component (water, vegetation) Klausmeier model, water flow from bare to vegetated areas drives pattern formation. The more elaborate Rietkerk and Gilad three-component models make a distinction between soil and surface water. In this article the three models are approximated from within a unifying framework, with a focus on processes that drive pattern formation, in order to promote the understanding of similarities and differences between these models. Reduction from a model with a separate soil and surface water component, to a model with a single water component, preserves Turing instability in all but one of the cases studied. (c) 2020 The Author. Published by Elsevier B.V.

【 授权许可】

Free