高阶竞争作为种群动态中空间模式多样性的最小机制

中文摘要 AI 辅助

我们证明，仅负反馈就能产生通常归因于尺度依赖性激活-抑制的自组织形状的多样性。对于一大类核函数，成对竞争模型仅生成六边形点阵模式。高阶项消除了这一限制，并促进条纹和间隙的形成。结合基于个体的模拟和非线性分析，我们推导出模式选择阈值，并构建了完整的状态图，包括一种不寻常的点-条纹-点序列。因此，点模式并非接近临界点的可靠指标。

英文摘要

We show that negative feedback alone generates the diversity of self-organized shapes usually attributed to scale-dependent activation-inhibition. For a broad class of kernels, pairwise competition models only generate hexagonal spot arrays. Higher-order terms eliminate this restriction and promote stripes and gaps. Combining individual-based simulations and nonlinear analysis, we derive the pattern-selection thresholds and construct the full state diagram, including an unusual spots-stripes-spots sequence. Spot patterns are thus not a reliable indicator of proximity to a tipping point.

发表机构

• Center for Advanced Systems Understanding (CASUS), Helmholtz-Zentrum Dresden-Rossendorf (HZDR)（高级系统理解中心，德累斯顿-罗斯多夫亥姆霍兹中心）
• ICTP South American Institute for Fundamental Research & Instituto de Física Teórica, Universidade Estadual Paulista - UNESP（国际理论物理中心南美基础研究所与理论物理研究所，圣保罗州立大学）
• Department of Ecology, Institute of Biosciences, University of São Paulo（生态学系，生物科学学院，圣保罗大学）

机构由 AI 辅助整理，请以论文原文为准。