One-Year Assessment and Predictive Modeling of Macrobenthic Communities Under Thermal Discharge and Environmental Influences Near the Preoperational YanTai HY-Nuclear Power Plant in the Yellow Sea

Yu Xia^1*Xiaofei Yin²Xiaohui Liu³Mengxue Xu³Deqing Weng⁴Qian Liu^3*Wendan Chi^3*Haiyi Wu³

• ¹Ocean University of China Haide College, Qingdao, China
• ²First Institute of Oceanography Ministry of Natural Resources, Qingdao, China
• ³Qingdao Key Laboratory of Coastal Ecological Restoration and Security, Marine Science Research 3 Institute of Shandong Province, Qingdao, China
• ⁴The Second Geological Exploration Institute of China Metallurgical Geology Administration, Fuzhou, China

The YanTai HY-Nuclear Power Plant (HYNPP) is a newly constructed nuclear power plant that entered operation after 2021. To establish a preoperational ecological baseline for the HYNPP, this study examined macrobenthic community structure and its relationships with multiple environmental variables using year-round field surveys conducted from 2016 to 2017. Eighty-five species from eight phyla were recorded in total, with winter showing the highest species number and spring exhibiting peak biomass. Species composition displayed pronounced seasonal turnover, with replacement rates exceeding 93% between adjacent seasons. Principal coordinates analysis (PCoA) and hierarchical clustering confirmed significant seasonal variation and the localized aggregation of species near the HYNPP. Diversity indices (S, H′, D′, and J′) varied across seasons and spatial gradients, strongly influenced by sea bottom temperature (SBT), salinity, dissolved oxygen (DO), and nutrient concentrations. Spearman correlation analysis and random forest (RF) modeling revealed SBT, DO, phosphate, and phytoplankton cell as dominant factors shaping macrobenthic diversity. RF models provided key insights into nonlinear interactions and variable importance across seasons. Leveraging the dependence-preserving power of copulas, Copula-Based Random Forest (CBRF) models were further developed under a +4 °C warming scenario to simulate post-operational thermal-discharge effects; the CBRF framework captured complex spatial responses, predicting localized biomass increases in sheltered muddy areas and biomass reductions in the outer bay. Mollusk biomass was projected to peak in spring near mixed-substrate habitats, while annelids and arthropods showed variable responses linked to sediment type and nutrient availability. These findings highlight strong spatiotemporal coupling between environmental parameters and macrobenthic assemblages, emphasizing the roles of SBT and phytoplankton-driven organic inputs in modulating community structure. The predictive framework built here supports long-term ecological risk assessments and management strategies for mitigating thermal discharge impacts in the Yellow Sea region.