Using an Ecosystem Modeling Approach to Explore Possible Ecosystem Impacts of Fishing in the Beibu Gulf, Northern South China Sea

Using the Ecopath with Ecosim software, a trophic structure model of the Beibu Gulf was constructed to explore the energy flows and provide a snapshot of the ecosystem operations. Input data were mainly from the trawl survey data collected from October 1998 to September 1999 and related literatures. The impacts of various fishing pressure on the biomass were examined by simulation at different fishing mortality rates. The model consists of 20 functional groups (boxes), each representing organisms with a similar role in the food web, and only covers the major trophic flows in the Beibu Gulf ecosystem. It was found that the food web of the Beibu Gulf was dominated by the primary producers path, and phytoplankton was the primary producer mostly used as a food source. The fractional trophic levels ranged from 1.0 to 4.02, and the marine mammals occupied the highest trophic level. Using network analysis, the ecosystem network was mapped into a linear food chain, and six discrete trophic levels were found with a mean transfer efficiency of 11.2%. The Finn cycling index was 9.73%. The path length was 1.821. The omnivory index was 0.197. The ecosystem had some degree of instability due to exploitation and other human activities, according to Odum's theory of ecosystem development. A 10-year simulation was performed for each fishery scenario. The fishing mortality rate was found to have a strong impact on the biomass. By keeping the fishing mortality rate at the current level for all fishing sectors, scenario 1 had a drastic decrease in the large fish groups. The biomass of the small and medium pelagic fish would increase to some extent. The biomass of the small and low trophic level species, jellyfish, prawns and benthic crustaceans would be stable. The total biomass of the fishery resources would have a 10% decrease from the current biomass after 10 years. In contrast, the reduced fishing mortality rate induced the recovery of biomass (scenarios 2-4). In scenario 2, the biomass of the large demersal fish and the large pelagic fish would increase to over 16 times and 10 times, respectively, of their current level. In scenario 4, the biomass of the large pelagic fish would increase to over 3 times of its current level. The total biomass of the fish groups, especially the high trophic level groups, would become significantly higher after 10 years, which illustrates the contribution on biomass recovery by relaxing the fishing pressure.