Fish Community Resource Utilization Reveals Benthic-Pelagic Trophic Coupling Along Depth Gradients in the Beibu Gulf, South China Sea

Benthic-pelagic coupling is a key approach to studying the structure and energy dynamics of shallow marine food webs. The movement and foraging patterns of consumers are major drivers of nutrient and energy distribution in ecosystems and are critical for maintaining ecosystem stability. To better understand the energy coupling of consumers between coastal marine habitats, this study employed a Bayesian mixture model using SC and SI data. By classifying functional groups based on taxonomy, morphological traits, and feeding ecology similarities, we constructed a trophic network and analyzed the changes in fish feeding patterns and the dynamics of benthic-pelagic coupling across environmental gradients. The results show that the primary carbon sources in the Beibu Gulf are phytoplankton, particulate organic matter (POM), and sediment organic matter (SOM), with phytoplankton contributing the most. Pelagic food subsidies dominate the food web. Small sized, abundant planktivorous and benthivorous fish act both as predators and important prey, transferring carbon and energy derived from both benthic and pelagic zones to higher trophic-levels. Larger, higher-trophic-level piscivorous fish serve as key energy couplers, preying on organisms from various habitats. Depth and chlorophyll-a (Chl-a) are the two key variables influencing the trophic structure of fish, with opposite gradient patterns observed for each. Along the depth gradient, fish exhibit clear adaptive foraging strategies. As water depth increases, fish tend to forage more within their specific habitat (either benthic or pelagic), with prey types continually changing, leading to a gradual reduction in the strength of benthic-pelagic trophic coupling. This study reveals the spatial resource utilization patterns and adaptive foraging strategies of fish in the Beibu Gulf, providing deeper insights into the structure and spatial variation of food webs. It also enhances our understanding of ecosystem responses to human pressures and global changes, offering valuable perspectives for predicting these responses.