Rate-Induced Transitions in Networked Complex Adaptive Systems: Exploring Dynamics and Management Implications Across Ecological, Social, and Socioecological Systems

• Main Authors: Vasconcelos, Vítor V, Marquitti, Flávia M. D, Ong, Theresa, McManus, Lisa C, Aguiar, Marcus, Campos, Amanda B, Dutta, Partha S, Jovanelly, Kristen, Junquera, Victoria, Kong, Jude, Krueger, Elisabeth H, Levin, Simon A, Liao, Wenying, Lu, Mingzhen, Mittal, Dhruv, Pascual, Mercedes, Pinheiro, Flávio L, Rocha, Juan, Santos, Fernando P, Sloot, Peter, Chenyang, Su, Taylor, Benton, Tekwa, Eden, Terpstra, Sjoerd, Tilman, Andrew R, Watson, James R, Yang, Luojun, Yitbarek, Senay, Zhan, Qi
• Format: Journal Article
• Language: English
• Published: 14-09-2023
• Subjects: Computer Science - Multiagent Systems; Mathematics - Dynamical Systems; Physics - Adaptation and Self-Organizing Systems; Physics - Physics and Society
• DOI: 10.48550/arxiv.2309.07449

Complex adaptive systems (CASs), from ecosystems to economies, are open
systems and inherently dependent on external conditions. While a system can
transition from one state to another based on the magnitude of change in
external conditions, the rate of change -- irrespective of magnitude -- may
also lead to system state changes due to a phenomenon known as a rate-induced
transition (RIT). This study presents a novel framework that captures RITs in
CASs through a local model and a network extension where each node contributes
to the structural adaptability of others. Our findings reveal how RITs occur at
a critical environmental change rate, with lower-degree nodes tipping first due
to fewer connections and reduced adaptive capacity. High-degree nodes tip later
as their adaptability sources (lower-degree nodes) collapse. This pattern
persists across various network structures. Our study calls for an extended
perspective when managing CASs, emphasizing the need to focus not only on
thresholds of external conditions but also the rate at which those conditions
change, particularly in the context of the collapse of surrounding systems that
contribute to the focal system's resilience. Our analytical method opens a path
to designing management policies that mitigate RIT impacts and enhance
resilience in ecological, social, and socioecological systems. These policies
could include controlling environmental change rates, fostering system
adaptability, implementing adaptive management strategies, and building
capacity and knowledge exchange. Our study contributes to the understanding of
RIT dynamics and informs effective management strategies for complex adaptive
systems in the face of rapid environmental change.