Temporal variations of food web in a marine bay ecosystem based on LIM-MCMC model

Climate change has led to significant fluctuations in marine ecosystems, including alterations in the structure and function of food webs and ecosystem status. Coastal ecosystems are critical to the functioning of the earth’s life-supporting systems. However, temporal variations in most of these ecosystems have remained unclear so far. In this study, we employed a linear inverse model with Markov Chain Monte Carlo (LIM-MCMC) combined with ecological network analysis (ENA) to reveal the temporal variations of the food web in Haizhou Bay of China. Food webs were constructed based on diet composition data in this ecosystem during the year of 2011 and 2018. Results indicated that there were obvious temporal variations in the composition of food webs in autumn of 2011 and 2018. The number of prey and predators for most species in food web decreased in 2018 compared with 2011, especially for Trichiurus lepturus, zooplankton, Amblychaeturichthys hexanema, and Loligo sp. ENA showed that the complexity of food web structure could be reflected by comprehensive analysis of compartmentalized indicators. Haizhou Bay ecosystem was more mature and stable in 2011, while the ecosystem’s self-sustainability and recovery from disturbances were accelerated from 2011 to 2018. These findings contribute to our understanding of the dynamics of marine ecosystems and highlight the importance of comprehensive analysis of marine food webs. This work provides a framework for assessing and comparing temporal variations in marine ecosystems, which provides essential information and scientific guidance for the Ecosystem-based Fisheries Management (EBFM).