Multi-Indicator Weighted Robustness Analysis of Planktonic Community Systems under Different Destructive Factors
Source abstract
Abstract
Marine plankton communities play a vital role in global carbon and nutrient cycles. Ensuring the robustness of these intricate ecosystems is critical for sustainable environmental management. In this paper, we apply complex network analysis to assess plankton community resilience against disturbances. We construct ecological interaction networks and simulate disruptions using four attack strategies targeting vertices and edges. Our multi-indicator evaluation scheme provides a more nuanced measure of robustness compared to single metrics. Our experiments revealed varying vulnerabilities across networks. Targeted attacks caused abrupt collapse, while random failures led to gradual decline. Identifying critical species and linkages is key to guiding protection efforts. Overall, plankton networks proved fragile, especially against deliberate attacks on central hubs. In our simulations, betweenness-based attacks were the most destructive. The multi-indicator robustness coefficient achieved better performance than individual metrics, with under 3% variance. This network methodology reveals hidden topological vulnerabilities and complements traditional plankton research. The quantitative insights provided in this paper can support marine conservation and governance.
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Research context
OpenAlex topics: Coral and Marine Ecosystems Studies · Complex Network Analysis Techniques · Microbial Community Ecology and Physiology
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
College of Information Technology, Shanghai Ocean University, Shanghai 201306, China
College of Electronic and Information Engineering, Shanghai University of Electric Power, Shanghai 200090, China
Funding
National Key Research and Development Project of China · Young Scientists Fund of the National Natural Science Foundation of China
References (36)
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