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To address uncertainties in how threatened coastal China seas fish communities respond to stressors like overfishing and climate change, this study applied Hierarchical Modelling of Species Communities (HMSC) to disentangle the assembly rules shaping these communities, filling a critical gap in understanding their spatiotemporal dynamics. We analyzed data on 384 fish species (1980-2018) and key environmental factors, with variance partitioning revealing that environmental filtering dominated fish distributions (explaining over 99% of variance), far outweighing random effects (0.60%). Among environmental drivers, sea surface temperature (49.00%) and sea surface salinity (33.25%) were the most influential, while seafloor substrate and water depth played secondary roles; notably, fewer species occupied fine sand habitats, and more preferred silt habitats. Residual species associations-indicative of potential biotic interactions-were most frequent within Gobiidae, likely due to this highly diverse taxon's specialized resource utilization and wide distribution, highlighting that biotic filtering is concentrated and ecologically relevant within this group. This work demonstrates HMSC's utility in unraveling coastal fish community assembly, providing a robust basis for predicting community changes and guiding biodiversity conservation efforts that support ocean health and dependent human activities.
Lin et al. (Sun,) studied this question.