The relationships between the distribution of marine fish and environmental factors have long been a focal point in marine ecology research. The hierarchical multispecies community model (HMSC), a multivariate hierarchical generalized linear mixed-effects model grounded in Bayesian statistics, enables simultaneous analysis of how environmental conditions, interspecific relationships, and phylogeny influence species distribution patterns. To investigate the environmental adaptability of fish species and their interspecific interactions in the coastal waters of Guangdong, we constructed five HMSC models. These models were developed using fisheries independent data from bottom trawl surveys conducted during four spring cruises in 2018, 2019, 2020, and 2022, and related environmental data on water depth, surface salinity, and surface temperature. The research results showed models with random effects fit the data better than those without random effects. The introduction of random effects enables the models to detect hidden variables that have not been observed yet, thereby improving the models' ability to fit complex ecological relationships. However, during the cross-validation process, these hidden variables could not be accurately estimated. As a result, the prediced R2 values of models without random effects were close to those of models with random effects. In particular, when random effects were added to the models related to predators at higher trophic levels, the model fit improved considerably. This indicates that interspecific relationships have a remarkable effect on the distribution of predators. Water depth is a crucial factor affecting the distribution of fish in the coastal waters of Guangdong, accounting for 62.1% of the variance in fish distribution. Moreover, most fish species exhibited nonlinear relationships with water depth. Changes in water depth often triggered a series of chain reactions in related factors such as temperature and salinity. The explanatory powers of surface temperature and surface salinity were relatively weak, accounting for only 3.5% and 3.3% of the variance, respectively. This might be due to the limitation of the survey time, as the environmental impacts on fish vary across different seasons. The random effects of some fish species had a relatively high explanatory rate. This suggests that, in addition to being influenced by water depth, surface temperature, and surface salinity, the distribution and survival of these fish species might also be affected by other potential factors. The relationships among fish populations could be broadly classified into two distinct groups. The first group of fish species predominantly exhibited positive correlations with other species. These fish were mostly small in size and inhabited the bottom or near-bottom layers of the water column. Their similar spatial distributions and comparable body sizes likely contributed to the significant positive associations observed among them. This suggests that shared ecological niches and habitat preferences play a crucial role in fostering co-occurrence patterns within this group. In contrast, the second group of fish species showed predominantly negative correlations with others. This phenomenon was likely linked to their positions in the food chains. Some species within this group occupied lower trophic levels, making them prey for a wide range of other fish, while others were higher-level predators. Such trophic interactions, whether as prey or predator, created competitive or predatory relationships that lead to negative correlations in their distributions. These findings underscore the inadequacy of relying solely on individual environmental factors to explain fish distribution patterns. Instead, both water depth and interspecific relationships emerge as key determinants of fish distribution in the coastal waters of Guangdong. Water depth influences various environmental conditions, while interspecific interactions shape the co-existence and distribution of species. Overall, the results of this study provide essential theoretical insights and empirical data that can inform the sustainable management of fish resources and the conservation of marine ecosystems in the coastal waters of Guangdong.