[POS] Ecology and Enviromment

[POS-33] Network Analysis of Freshwater Ecosystem Metaweb Data and Parameter Estimation of a Mathematical Model

*Natsuki Yajima¹, YoungSeuk Park², Kei Tokita¹ (1. Graduate School of Informatics, Nagoya Univ (Japan), 2. Department of Biology, Kyung Hee Univ (Korea))

Keywords:

metaweb,interactions,graph theory,lotka-volterra model

In recent years, there has been growing concern over the impacts of environmental changes and anthropogenic pressures on ecosystems. Among the Sustainable Development Goals (SDGs) proposed by the United Nations, several emphasize the importance of ecosystem conservation. Since around 2019, Metaweb data—records of potential interactions within regional biological communities—have become a focus of active research, aimed at supporting the conservation and management of ecosystems. This study analyzes the structural properties of network data from KF-metaweb, the first Metaweb dataset in Asia, which represents freshwater ecosystems in South Korea. The analysis reveals that the KF-metaweb does not exhibit scale-free characteristics, has a short average path length, and a relatively low directed clustering coefficient. Furthermore, it was demonstrated that removing links based on trophic levels reduces network connectivity more efficiently than random removal, suggesting that trophic levels may play a significant role in maintaining the connectivity of freshwater ecosystems in South Korea. Additionally, interaction data were aggregated into six taxonomic groups, and parameter estimation of a six-species Lotka–Volterra (LV) system was performed using Simulated Annealing. Although parameters corresponding to an internal equilibrium point were discovered, behaviors indicative of chaos were not observed. This suggests that further model refinement and the incorporation of time-series data may be necessary. This study contributes to understanding the structural characteristics of networks derived from the KF-metaweb dataset.