Abstract

On September 23, 2019, the World Meteorological Organization WMO published the Global Climate Report 2015-2019, which explained the trend of global warming. The phenomenon of rising global ocean temperature in the report is also an issue that needs to be researched. It will make certain marine life be forced to migrate from their habitats, thus affecting the development of economic industries such as fisheries. As consultants to the Scottish North Atlantic Fisheries Management Association, in this work, we have launched a corresponding study on this issue. Corresponding mathematical models have been established, which can well predict the future distribution of fish populations. Questions are essentially predictions of the future distribution of North Atlantic fish stocks and their impact on fishing companies. So our first task is to build an identification and prediction model of future fish habitat space model (IPM-FFHS Model). Because this distribution is caused by changes in ocean temperature, we have established a prediction model for the average sea surface temperature of the North Atlantic region (AMO-BP Model) based on BP neural network to predict future SST. At the same time, other influential factors of the distribution can modify the model. The AMO-BP Model was then combined with the current distribution of the habitat of the fish to draw a predicted spatial image of the future habitat range. At last, we combined the IPM-FFHS Model to obtain the abandonment temperature threshold of the fishery to obtain the duration of fish migration and the survival environment under different effects.

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