{"title":"Systems coupling and cross-diffusion drives complex nested pattern self-organization in predator-prey systems","authors":"Tousheng Huang, Yifan Yang, Zhenyu Ren, Ruyin Li, Zequn Lin, Wang Tian","doi":"10.1016/j.ecocom.2025.101125","DOIUrl":null,"url":null,"abstract":"<div><div>The pattern self-organization of spatially extended predator-prey systems has been under intensive investigations in recent decades, but the spatiotemporal dynamics in the case of systems coupling is still lack of understanding. In this research, we focus on the pattern self-organization when two reaction-diffusion predator-prey systems are coupled together via population vertical migration. The dispersion relation and Turing instability conditions are derived, and we find the emergence of nested patterns when the dispersion relation shows two peaks. Moreover, the positive cross-diffusion enlarges parametric region for the nested patterns and enhances the pattern complexity. Numerical simulations reveal rich types of new patterns, such as white-eye pattern, nested spot pattern, and nested stripe-spot pattern. The obtained results may provide a theoretical basis for explaining the nested structures and complex patchiness phenomena occurring in aquatic ecosystems.</div></div>","PeriodicalId":50559,"journal":{"name":"Ecological Complexity","volume":"62 ","pages":"Article 101125"},"PeriodicalIF":3.1000,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ecological Complexity","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1476945X25000108","RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ECOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
The pattern self-organization of spatially extended predator-prey systems has been under intensive investigations in recent decades, but the spatiotemporal dynamics in the case of systems coupling is still lack of understanding. In this research, we focus on the pattern self-organization when two reaction-diffusion predator-prey systems are coupled together via population vertical migration. The dispersion relation and Turing instability conditions are derived, and we find the emergence of nested patterns when the dispersion relation shows two peaks. Moreover, the positive cross-diffusion enlarges parametric region for the nested patterns and enhances the pattern complexity. Numerical simulations reveal rich types of new patterns, such as white-eye pattern, nested spot pattern, and nested stripe-spot pattern. The obtained results may provide a theoretical basis for explaining the nested structures and complex patchiness phenomena occurring in aquatic ecosystems.
期刊介绍:
Ecological Complexity is an international journal devoted to the publication of high quality, peer-reviewed articles on all aspects of biocomplexity in the environment, theoretical ecology, and special issues on topics of current interest. The scope of the journal is wide and interdisciplinary with an integrated and quantitative approach. The journal particularly encourages submission of papers that integrate natural and social processes at appropriately broad spatio-temporal scales.
Ecological Complexity will publish research into the following areas:
• All aspects of biocomplexity in the environment and theoretical ecology
• Ecosystems and biospheres as complex adaptive systems
• Self-organization of spatially extended ecosystems
• Emergent properties and structures of complex ecosystems
• Ecological pattern formation in space and time
• The role of biophysical constraints and evolutionary attractors on species assemblages
• Ecological scaling (scale invariance, scale covariance and across scale dynamics), allometry, and hierarchy theory
• Ecological topology and networks
• Studies towards an ecology of complex systems
• Complex systems approaches for the study of dynamic human-environment interactions
• Using knowledge of nonlinear phenomena to better guide policy development for adaptation strategies and mitigation to environmental change
• New tools and methods for studying ecological complexity