Saury center fishing ground prediction method based on a habitat index

Abstract

The invention discloses a saury center fishing ground prediction method based on a habitat index model. The saury center fishing ground prediction method comprises the steps of acquiring historical production data of saury in N months and environment factors corresponding to the production data; Respectively establishing relationships between the adaptive indexes of all months and SST, SSTG and SSH based on the environmental factors and the yield density; Fitting the relationship between the environmental factor and the adaptability index by using a nonlinear least square method, and estimating parameters a, b and c in a yield density equation; And determining weight values Wst, m, Wsstg, m, Wssh and m of the SST, SSTG and SSH in the habitat indexes based on the contribution rates of the SST, SSTG and SSH relative adaptability indexes calculated by the BRT to obtain the habitat indexes. According to the method, the adaptive index is established by adopting the yield density equation, the environmental factor weight of each month is reasonably selected in combination with the BRT method, the environmental factor ranges of the mackerel suitable for the habitat in different operationmonths are calculated respectively, the habitat index model distribution of the mackerel is predicted, and technical support is provided for production operation.

Description

technical field [0001] The invention relates to the fields of marine fishery and marine science and technology, in particular, the invention relates to a method for predicting a central fishery of saury based on a habitat index model. Background technique [0002] Fishery forecast is based on the relationship and law between fish and marine environmental elements, and forecasts the status of aquatic resources in a certain period of time in the future and in water areas, mainly including fishing seasons, central fishing grounds, resource abundance and possible catches, etc. An important part of fish production. [0003] Pacific saury is a cold-water highly migratory pelagic fish, widely distributed in the subtropical and temperate Oyashio and Kuroshio waters of the Northwest Pacific Ocean. Pacific saury can spawn in spring, autumn, and winter throughout the year. It has a short life cycle, strong resource resilience, and significant year-to-year resource fluctuations. Some s...

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Problems solved by technology

[0015] Neural network model: The expression, storage, and reasoning and calculation of knowledge are all implicit, and cannot explain its own reasoning basis and reasoning process. It has the disadvantages of slow convergence and local extreme values;

[0016] Linear regression model: The relationship between fishing grounds and marine environmental factors is generally random and fuzzy. Sometimes the model cannot meet the data assumptions, or it is difficult to establish a regression equation with high correlation. In reality, environmental factors and fish distribution are mostly It is a nonlinear relationship, and some linear fitting models may not be satisfied;

[0017] Habitat index model with equal weights: The effects of various environmental factors on fish distribution are not completely consistent, and different environmental factors should be given different weights. However, the weights of environmental factors in previous habitat index models were mainly determined by expert knowledge. Assigned or defaulted to equal weights, which cannot reflect the difference in the contribution rate of each environmental factor to habitat quality;

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