{"title":"向北移动,但从未远离我们","authors":"Yongheng Wang, Yuxiao Li, Yuewen Yang, Zhifan Zhang","doi":"10.23977/fbb2020.003","DOIUrl":null,"url":null,"abstract":"Over the past 20 years, the way North Atlantic mackerel and herring migrate has changed dramatically. In the 1980s, the migration occurred in the late summer and autumn. Now, the start of the migration is lagging, and their migration routes move further offshore. Firstly, we establish a support vector machine (SVM) model to predict the temperature of a single geographic coordinate point, and then applied it to the whole North Atlantic Ocean. After predicting the sea surface temperatures in the next 50 years, we conduct cluster analysis using ARCGIS, the geographic information analysis tool, to optimize our SVM model. We find that 10 isotherm gradually move northward in the next 50 years, specifically, the habitat of the two fish species will move 2.5◦northward in the future, further away from the mainland. Secondly, we design an operation evaluation model for a small fisheries company based on previous forecast, and assume the best scenario, that is, the rate of global warming to maintain the status QUO, and the worst scenario, 1.5 times faster global warming speed. Our model shows that in the best case, it is unprofitable for the company continuously go fishing after 45 years, and in the worst case, only 5 years. Finally, given that fishing places might move to another country, and give constructive operation suggestions like fishing by time, by categories and by quota.","PeriodicalId":376375,"journal":{"name":"2020 2nd International Symposium on the Frontiers of Biotechnology and Bioengineering (FBB 2020)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Moving North But Never Far From Us\",\"authors\":\"Yongheng Wang, Yuxiao Li, Yuewen Yang, Zhifan Zhang\",\"doi\":\"10.23977/fbb2020.003\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Over the past 20 years, the way North Atlantic mackerel and herring migrate has changed dramatically. In the 1980s, the migration occurred in the late summer and autumn. Now, the start of the migration is lagging, and their migration routes move further offshore. Firstly, we establish a support vector machine (SVM) model to predict the temperature of a single geographic coordinate point, and then applied it to the whole North Atlantic Ocean. After predicting the sea surface temperatures in the next 50 years, we conduct cluster analysis using ARCGIS, the geographic information analysis tool, to optimize our SVM model. We find that 10 isotherm gradually move northward in the next 50 years, specifically, the habitat of the two fish species will move 2.5◦northward in the future, further away from the mainland. Secondly, we design an operation evaluation model for a small fisheries company based on previous forecast, and assume the best scenario, that is, the rate of global warming to maintain the status QUO, and the worst scenario, 1.5 times faster global warming speed. Our model shows that in the best case, it is unprofitable for the company continuously go fishing after 45 years, and in the worst case, only 5 years. Finally, given that fishing places might move to another country, and give constructive operation suggestions like fishing by time, by categories and by quota.\",\"PeriodicalId\":376375,\"journal\":{\"name\":\"2020 2nd International Symposium on the Frontiers of Biotechnology and Bioengineering (FBB 2020)\",\"volume\":\"25 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 2nd International Symposium on the Frontiers of Biotechnology and Bioengineering (FBB 2020)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23977/fbb2020.003\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 2nd International Symposium on the Frontiers of Biotechnology and Bioengineering (FBB 2020)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23977/fbb2020.003","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Over the past 20 years, the way North Atlantic mackerel and herring migrate has changed dramatically. In the 1980s, the migration occurred in the late summer and autumn. Now, the start of the migration is lagging, and their migration routes move further offshore. Firstly, we establish a support vector machine (SVM) model to predict the temperature of a single geographic coordinate point, and then applied it to the whole North Atlantic Ocean. After predicting the sea surface temperatures in the next 50 years, we conduct cluster analysis using ARCGIS, the geographic information analysis tool, to optimize our SVM model. We find that 10 isotherm gradually move northward in the next 50 years, specifically, the habitat of the two fish species will move 2.5◦northward in the future, further away from the mainland. Secondly, we design an operation evaluation model for a small fisheries company based on previous forecast, and assume the best scenario, that is, the rate of global warming to maintain the status QUO, and the worst scenario, 1.5 times faster global warming speed. Our model shows that in the best case, it is unprofitable for the company continuously go fishing after 45 years, and in the worst case, only 5 years. Finally, given that fishing places might move to another country, and give constructive operation suggestions like fishing by time, by categories and by quota.