Uniqueness measure based on the weighted trophic field overlap of species in the food web

Abstract

With the application of the topological network concept to study food webs, species uniqueness in terms of irreplaceability has begun to be considered when identifying important species in the ecosystem. Based on the uniqueness method of quantifying the interactions and trophic field overlap of species in food webs, we propose using the weighted trophic field overlap (WTO) to determine the uniqueness of species in a topological network by considering the proportions of prey in the diets of predators. This proposed method involves measuring the uniqueness of species structurally and mathematically to overcome the deficiencies of the traditional method (the sum of trophic field overlap, STO), which only relies on the topological structure of the food web. We compared the species ranking results obtained via the WTO and STO methods using the Wilcoxon signed-rank test and compared the Spearman rank correlation coefficients between them and three other topological indices. In this study, we focused on the food web of Haizhou Bay ecosystem. The results showed that Leptochela gracilis, Acetes sp., Alpheus japonicus, Engraulis japonicus, and Alpheus distinguendus were the most unique species in the food web of Haizhou Bay. They had the lowest WTO values, and three of these species were not identified as unique by the traditional method. However, they play important roles as prey in Haizhou Bay ecosystem and have high interaction strengths with other species in the food web weighted by the proportion of prey, which are not recognized by the traditional method. The proposed index is sensitive to changes in the diets of predators since slight fluctuations may cause the index to vary considerably. The proposed methodology could be extended to other marine ecosystems to identify unique species from a practical and dynamic perspective and will contribute to the protection of unique species that maintain the trophic diversity of food webs and ecosystem robustness.