多因素下鱼类迁徙预测模型
Prediction Model of Fish Migration under Multiple Factors
摘要: 每一种生物都对自身的生存环境存在一定的要求,全球海洋温度的升高使得一些海洋生物离开原来生活的地方,去寻找更适宜生存的栖息地。海洋生物的这一迁徙现象给依赖这一资源生存的渔业公司造成很大困扰。鲱鱼和鲭鱼为苏格兰经济作出重要贡献,对当地渔业公司至关重要,随着近年来海水温度不断上升,这两种鱼类也将往北逐渐进行迁徙。为了让苏格兰当地小型渔业公司对这一迁徙现象及早做出有效应对措施,我们通过收集近几年这两种鱼的数量以及当地海水温度数据建立模型,对两类鱼迁徙位置进行了预测。同时通过引入海温变化速率这一参数,我们研究了鱼类迁徙速度与海水温度上升速度之间的关系。利用上述模型,我们可以掌握鱼群未来分布位置以及海水温度变化快慢对鱼群迁徙速率的影响,为小型渔业公司制定有效应对策略提供依据。
Abstract: Every living creature has certain requirements for its own living environment. The global warming of ocean temperature makes some Marine creatures leave their original living place to find a more suitable habitat. This migration of Marine life is causing problems for fishing companies that depend on the resource. Herring and mackerel are important to the Scottish economy and vital to local fishing companies, and are due to migrate north as sea temperatures have risen in recent years. In order to enable small local fishing companies in Scotland to respond effectively and early to this migration phenomenon, the migration location of the two species of fish was predicted by collecting data on their populations and local sea temperature in recent years. At the same time, by introducing the parameter of SST change rate, we studied the relationship between fish migration rate and seawater temperature rise rate. Using the above model, we can grasp the future distribution location of fish stocks and the impact of sea temperature change on the migration rate of fish stocks, so as to provide a basis for small fishery companies to formulate effective coping strategies.
文章引用:张欣欣, 赵依宁, 蔡冰清. 多因素下鱼类迁徙预测模型[J]. 应用数学进展, 2020, 9(5): 733-741. https://doi.org/10.12677/AAM.2020.95087

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