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The outbreak of nuclear power cooling water system (NPCS) disaster-causing organisms has become more frequent, causing huge economic losses. Therefore, it is necessary to understand the aggregation mechanism of disaster-causing organisms for the risk prevention and control of NPCS. Hence, this study applied the Lagrangian flow network (LFN) to analyze the aggregation mechanism of Acetes near NPCS, as such a complex network can describe the interconnections between massive nodes and has already been used for modeling complex nonlinear systems, revealing how the mechanisms of such novel processes emerge. In this study, the degree and probability paths in the network were used to reveal the transport pathway and aggregation area of Acetes. The experimental results highlighted that the sea area of the nuclear power plant is the key node with a large in-degree of the LFN, where the material easily accumulated. The Acetes near the NPCS mainly originated from the east along two critical paths. Overall, this study demonstrates that the LFN is a feasible approach to predicting the transport and the accumulation of the NPCS disaster-causing plankton.

Material transport around the headland has received more attention. To reveal the material transport pattern and its response to the topography in the Yellow River Estuary (YRE), in this paper, three Lagrangian analysis methods, including Lagrangian residual current, particle tracking model, and Lagrangian coherent structures (LCSs), are used to analyze the material horizontal transport near the headland in the YRE. The results of the study show that the headland plays an important role in the hydrodynamic processes and material transport in the YRE. Due to the current shear induced by the topography, materials easily diffuse, forming a front around the headland. Due to the blocking and shading effects of the headland, the materials tend to accumulate on the right side of the headland (facing the sea). The above three Lagrangian methods can describe the characteristics of the material distribution, but the LCS method is superior in comparison. Due to their more stable spatial structure, LCSs can be used to analyze the transport of pollutants, larvae, microplastics, etc. in the YRE.

Marine fishes are sensitive to the environment during their early life stages. This study adopts a habitat suitability index (HSI) model to evaluate the environmental suitability for early stages of anchovy (Engraulis japonicus) in Laizhou Bay. Instead of calculating the suitability of spawning grounds and nursery grounds independently or the simple average of the two, an individual-based model is used to simulate the drifting trajectories of anchovy eggs to establish the link between a spawning ground and its corresponding nursery ground. The HSI of early life habitat is determined by averaging the HSI value of the paired two grounds. The model results suggest that a small patch at eastern Laizhou Bay (near 120.1 E°, 37.6 N°) is the most critical and suitable area for anchovy in early life stages. It can provide an appropriate habitat for anchovy eggs and allow the eggs to migrate to the inside of the bay with plenty of plankton, which would benefit the newly hatching larvae. The results indicate the significant impact of hydrodynamic transport on fishery recruitment process, which should not be neglected in habitat quality evaluation. The model adopted in this study is applied to anchovy as a case study, but it is also exportable to other species of commercial interest.

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