The multiscale nature of ecohydrological processes and feedbacks implies that vegetation patterns arising in water‐limited systems are directly linked to water redistribution processes occurring at much shorter timescales than vegetation growth. This in turn suggests that the initially available water in the system can play a role in determining the trajectory of the system, together with the well‐known role of the rainfall gradient. This work explores the role of initial hydrological conditions on vegetation dynamics and vegetation patterns. To do so, the HilleRisLambers–Rietkerk model was solved with different rainfall amounts and a large range of initial hydrological conditions spanning from near‐equilibrium to far‐from‐equilibrium conditions. The resulting vegetation patterns and ecohydrological signatures were quantitatively studied. The results show that not only do initial hydrological conditions play a role in the ecohydrological dynamics but also they can play a dominating one even resulting in divergent vegetation patterns that exhibit convergent mean‐field properties, including a new set of hybrid patterns. Our results highlight the relevance of assessing both global ecological and hydrological signatures and quantitatively assessing patterns to describe and understand system dynamics and in particular to determine if the systems are transient or steady. Furthermore, our analysis shows that the trajectories the system follows during its transient stages cannot be neglected to understand complex dependencies of the long‐term steady state to environmental factors and drivers.

中文翻译：

---

从非平衡初始条件到稳定的旱地植被模式：轨迹如何重要

生态水文过程和反馈的多尺度性质意味着，水受限系统中出现的植被格局与发生在比植物生长短得多的时间尺度上的水再分配过程直接相关。这反过来表明，系统中最初可用的水可以与确定降雨梯度一起在确定系统轨迹方面发挥作用。这项工作探讨了初始水文条件对植被动态和植被格局的作用。为此，用不同的降雨量和大范围的初始水文条件（从接近平衡状态到远离平衡状态）求解了HilleRisLambers–Rietkerk模型。定量研究了产生的植被格局和生态水文特征。结果表明，不仅初始水文条件在生态水文动力学中起作用，而且它们甚至可以发挥主导作用，甚至导致表现出趋同平均场特性的不同植被格局，包括一组新的混合格局。我们的结果强调了评估全球生态和水文特征以及定量评估模式以描述和理解系统动力学，尤其是确定系统是暂态还是稳定的相关性。此外，我们的分析表明，系统在瞬态阶段所遵循的轨迹不能忽略以了解长期稳态对环境因素和驱动因素的复杂依赖性。