The population dynamics of clustered consumer-resource spatial patterns: Insights from the demographics of a Turing mechanism

• 成果类型: Article
• 署名作者: Hajian-Forooshani, Zachary; Rivera-Salinas, Iris Saraeny; Perfecto, Ivette; Vandermeer, John
• 署名单位: University of Michigan System; University of Michigan; German Research Foundation (DFG); German Centre for Integrative Biodiversity Research (iDiv); Martin Luther University Halle Wittenberg; University of Michigan System; University of Michigan
• 刊物名称: PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
• ISSN/ISSBN: 0027-14106
• DOI: 10.1073/pnas.2407991121
• 发表日期: 2025-01-21
• 关键词: self-organization; scale; models; criticality; ecosystems; patchiness; complexity; vegetation; FRAMEWORK; genetics

摘要

In ecology, Alan Turing's proposed activation-inhibition mechanism has been abstracted as corresponding to several ecological interaction types to explain pattern formation ecosystems. Consumer-resource interactions have strong theoretical arguments linking them to both the Turing mechanism and pattern formation, but there is little empirical support to demonstrate these claims. Here, we connect several lines of evidence to support the proposition that consumer-resource interactions can create empirically observed spatial patterns through a mechanism similar to Turing's theory. We propose the existence of a fine- scale demographic spatial pattern (DSP), in which the youngest resources are located at the periphery and oldest in the center of clusters. We find evidence of DSP in the spatially clustered distribution of arboreal ant nests, whose large- scale spatial patterning has previously been hypothesized to be driven by ant parasitoids. Through combination of field surveys and analysis of demographic trends, we demonstrate how the DSP structures the interactions between the ant and its parasitoid. To explore the implications of DSP for consumer-resource pattern forming systems generally, we use a spatially explicit consumer-resource model to show how relative diffusion rates of the system shape multiscale spatial patterns that structure the demographic trends of the resource population in predictable ways. This work provides both empirical support for consumer-resource spatial patterns as well as a multiscale approach to understand their spatially explicit population dynamics.