Fishery migration under the influence of global warming

• Published in: IOP Conference Series: Earth and Environmental Science
• Main Authors: Tang, Jian, Zhu, Zeqi, Guo, Siyi
• Format: Article in Journal/Newspaper
• Language: unknown
• Published: IOP Publishing 2021
• Subjects: Fishing Range; North Atlantic
• Online Access: http://dx.doi.org/10.1088/1755-1315/631/1/012015; https://iopscience.iop.org/article/10.1088/1755-1315/631/1/012015/pdf; https://iopscience.iop.org/article/10.1088/1755-1315/631/1/012015

Abstract With the pace of global warming getting faster and faster, the temperature of the sea is gradually rising. Meanwhile, Scotland, located on the east coast of the North Atlantic, is facing a serious problem: how to develop their fishing industry while fish are migrating. In this article, we will use a series of models to analyze the current situation and recommend some ways for the development of small Scottish fishing companies. In Task 1, based on the sufficient global ocean temperature data recorded by the Met Office Hadley Centre, we firstly used the convolutional neural network (CNN) model to learn the ocean temperature change in the waters around Scotland in the past 50 years, to find out the changing trend and make a reasonable prediction on the sea temperature (SST) change in the next 50 years. Then, by using the obtained data in ocean temperature, continental shelves, and ocean currents, the behavior of herring and mackerel was excavated and simulated. Besides, we build a double-objective Linear Programming (DLP) model to predict the location of these two fish species in the next 50 years, based on the distribution patterns of the Scottish fisheries over the past 50 years. What’s more, we also performed the Process of Gridding on the map of Scotland, making all the models easier to calculate. In Task 2, we used the Logistic Growth Model (LGM) to establish a freshness model for captured fish, combined with the speed of a Scottish fishery boat to calculate the company's fishing range. Then we obtained the best and worst situations of the two fish habitats for the company's fishing business in the next 50 years through the fine-tuning of the parameters and sensitivity analysis. Also, we predicted the most likely future time for the company to be unable to continue fishing if maintaining a former strategy. In Task 3, we simulated the model in Task 2 to obtain a fish freshness model with refrigeration equipment, which provides basic elements needed for relocating a fishing port or updating fishing ...