Identifying the underlying mechanisms that influence the spatial patterns in populations improves the forecasts of the alternative management strategies on the spatial dynamics of the populations, which are critical f...Identifying the underlying mechanisms that influence the spatial patterns in populations improves the forecasts of the alternative management strategies on the spatial dynamics of the populations, which are critical for assessing and managing the fisheries and improving the water resource management. This paper described a new approach of the numerical model for the prediction of the aquatic animal distribution in the flows. The model was developed based on the kinetic theory of gases, the mechanism of the aquatic animal movement and the flow hydrodynamic patterns. The model was validated using the available experimental data and an acceptable agreement was obtained. A comprehensive parameter study was then conducted to help understand the impact and the sensitivity of each parameter to the aquatic animal distribution. The promising results of the model reveal the prospect of applying this model to the reliable prediction of the aquatic animal distribution within a relatively large water area.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.51139003&11372161)
文摘Identifying the underlying mechanisms that influence the spatial patterns in populations improves the forecasts of the alternative management strategies on the spatial dynamics of the populations, which are critical for assessing and managing the fisheries and improving the water resource management. This paper described a new approach of the numerical model for the prediction of the aquatic animal distribution in the flows. The model was developed based on the kinetic theory of gases, the mechanism of the aquatic animal movement and the flow hydrodynamic patterns. The model was validated using the available experimental data and an acceptable agreement was obtained. A comprehensive parameter study was then conducted to help understand the impact and the sensitivity of each parameter to the aquatic animal distribution. The promising results of the model reveal the prospect of applying this model to the reliable prediction of the aquatic animal distribution within a relatively large water area.
