Study on Fish Migration Caused by Sea Temperature Rise Based on Regression Analysis

Global warming has caused widespread concern around the world. The resulting changes in seawater temperature will seriously affect the migration of marine life, and as a result, some small fishing companies will have economic problems. We are honored to be hired as a consultant to analyze this and provide a feasible solution. We studied herring and mackerel in areas near Scotland. Firstly, we looked at the location information of the two types of fish school activity from 1970 to 2020, integrated them, and used the time series model and regression analysis model to predict the area and location of possible fish school activity in the next 50 years. The possible range of movement of the group, which helps the company to carry out timely stopping loss of the current fishing strategy and controlling the future economic regulation. In our prediction model, changes in sea surface temperature have a large impact on the migration behavior of fish schools. In order to prevent the timely fishing due to the influence of temperature, we give the best case, worst case, and most likely case after model prediction, and visualize the data by sorting, analyzing, and calculating. The process is more intuitive. Our forecasting model is affected by many factors, which will affect the economic benefits of the company. On the one hand, if changes are made to fishing vessels to keep the fish fresh and of high quality without land support, the cost in this case is too high; but on the other hand, if we transfer the company appropriate migration will not only allow the company to reduce costs, but also promote the exchange of regional cultures and jointly benefit. For the sake of climate change and economic benefits, we have given this plan. What is slightly inadequate is that the movement process of the animal group we considered is actually continuously changing in two-dimensional space and time. The process of establishing the model in three-dimensional space is not considered in the article. But the practicability and openness of the model are also its biggest advantages, and the sensitivity analysis in the process also makes the model more rigorous.