Extinction Chains Reveal Intermediate Phases Between the Safety and Collapse in Mutualistic Ecosystems
Guangwei Wang,
Xueming Liu,
Ying Xiao,
Ye Yuan,
Linqiang Pan,
Xiaohong Guan,
Jianxi Gao,
Hai-Tao Zhang
Affiliations
Guangwei Wang
The MOE Engineering Research Center of Autonomous Intelligent Unmanned Systems, State Key Laboratory of Digital Manufacturing Equipment and Technology, School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan 430074, China; Guangdong HUST Industrial Technology Research Institute, Huazhong University of Science and Technology, Dongguan 523808, China; Guangdong Provincial Engineering Technology Center of Autonomous Unmanned Vessels, Dongguan 523808, China
Xueming Liu
The MOE Engineering Research Center of Autonomous Intelligent Unmanned Systems, State Key Laboratory of Digital Manufacturing Equipment and Technology, School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan 430074, China
Ying Xiao
The MOE Engineering Research Center of Autonomous Intelligent Unmanned Systems, State Key Laboratory of Digital Manufacturing Equipment and Technology, School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan 430074, China
Ye Yuan
The MOE Engineering Research Center of Autonomous Intelligent Unmanned Systems, State Key Laboratory of Digital Manufacturing Equipment and Technology, School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan 430074, China
Linqiang Pan
The MOE Engineering Research Center of Autonomous Intelligent Unmanned Systems, State Key Laboratory of Digital Manufacturing Equipment and Technology, School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan 430074, China
Xiaohong Guan
MOE Key Laboratory of Intelligent Networks and Network Security & State Key Laboratory of Manufacturing Systems, Xi’an Jiaotong University, Xi’an 710049, China; Tsinghua National Laboratory of Information Science and Technology, Department of Automation, Tsinghua University, Beijing 100084, China
Jianxi Gao
Department of Computer Science, Rensselaer Polytechnic Institute, Troy, NY 12180, USA; Corresponding authors.
Hai-Tao Zhang
The MOE Engineering Research Center of Autonomous Intelligent Unmanned Systems, State Key Laboratory of Digital Manufacturing Equipment and Technology, School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan 430074, China; Corresponding authors.
Ecosystems are undergoing unprecedented persistent deterioration due to unsustainable anthropogenic human activities, such as overfishing and deforestation, and the effects of such damage on ecological stability are uncertain. Despite recent advances in experimental and theoretical studies on regime shifts and tipping points, theoretical tools for understanding the extinction chain, which is the sequence of species extinctions resulting from overexploitation, are still lacking, especially for large-scale nonlinear networked systems. In this study, we developed a mathematical tool to predict regime shifts and extinction chains in ecosystems under multiple exploitation situations and verified it in 26 real-world mutualistic networks of various sizes and densities. We discovered five phases during the exploitation process: safe, partial extinction, bistable, tristable, and collapse, which enabled the optimal design of restoration strategies for degraded or collapsed systems. We validated our approach using a 20-year dataset from an eelgrass restoration project. Counterintuitively, we also found a specific region in the diagram spanning exploitation rates and competition intensities, where exploiting more species helps increase biodiversity. Our computational tool provides insights into harvesting, fishing, exploitation, or deforestation plans while conserving or restoring the biodiversity of mutualistic ecosystems.
