WO2020088615A1 - Procédé de prédiction d'abondance des ressources en toutenons japonais (todarodes pacificus) et application basée sur l'oscillation décennale du pacifique - Google Patents

Procédé de prédiction d'abondance des ressources en toutenons japonais (todarodes pacificus) et application basée sur l'oscillation décennale du pacifique Download PDF

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WO2020088615A1
WO2020088615A1 PCT/CN2019/114867 CN2019114867W WO2020088615A1 WO 2020088615 A1 WO2020088615 A1 WO 2020088615A1 CN 2019114867 W CN2019114867 W CN 2019114867W WO 2020088615 A1 WO2020088615 A1 WO 2020088615A1
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squid
pdo
japanese
value
abundance
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PCT/CN2019/114867
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Chinese (zh)
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陈新军
魏广恩
余为
张忠
方舟
韦记朋
雷林
汪金涛
陆化杰
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上海海洋大学
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Priority claimed from CN201811300078.XA external-priority patent/CN109523070A/zh
Priority claimed from CN201811299884.XA external-priority patent/CN109472405A/zh
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Priority to JP2020561674A priority Critical patent/JP7157479B2/ja
Publication of WO2020088615A1 publication Critical patent/WO2020088615A1/fr

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/02—Agriculture; Fishing; Forestry; Mining
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
    • Y02A40/00—Adaptation technologies in agriculture, forestry, livestock or agroalimentary production
    • Y02A40/80—Adaptation technologies in agriculture, forestry, livestock or agroalimentary production in fisheries management
    • Y02A40/81—Aquaculture, e.g. of fish

Definitions

  • the invention belongs to the technical field of squid resource prediction, and relates to a method for predicting the abundance of Japanese squid resources based on the Pacific Oscillation Index and its application.
  • Todarodes pacificus (also known as Japanese squid) is an important economic cephalopod resource in the world, and it is only distributed in the northwestern Pacific Ocean and the Alaska Bay in the eastern Pacific Ocean. It is mainly distributed in the 21 ° -50 ° N waters of the western Pacific, namely the Japan Sea, the Pacific coast of Japan, and the Yellow Sea and East China Sea in China. It is a warm temperate oceanic shallow sea species, inhabiting the surface layer to 500m water layer, with a wide temperature range. According to the spawning season, growth type and migration path of Pacific pleated fish, it can be divided into three groups: winter group, autumn group and summer group. They have different life cycles, but have the same habits. The winter group is the most widely distributed.
  • Pacific pleated squid is one of the earliest species of cephalopods developed and utilized on a large scale in the world. Before the 1970s, its output accounted for 70-80% of the total domestic cephalopod production. According to FAO statistics, the total production of Pacific pleated squid reached its highest level in history in 1968, exceeding 750,000 tons. However, due to the increase in fishing intensity, future production will decline year by year. The lowest output since 1950 was reached in 1986, with only more than 120,000 tons. Since then, there has been a continuous increase, until 1996, annual production reached nearly 700,000 tons. After that, it declined again, and the current production of Pacific pleated squid is stable at 320,000 to 420,000 tons.
  • the main catch of the autumn shoal of Pacific pleated fish is from the Sea of Japan, and the main fishing season is from May to October.
  • Japan and South Korea are the main fishing countries. Others include North Korea and China, and there are also small amounts of fishing.
  • the coastal waters are mainly small squid fishing boats (less than 30 tons), and the catch is fresh. In the open sea, it is a medium-sized squid fishing boat (30 to 185 tons), and the catch is frozen.
  • squid fishing there are fixed net operations and bottom trawl operations.
  • Japan ’s output reached 300,000 tons, and then decreased. It was only about 50,000 tons in 1986, and then increased. It stabilized at 70,000 to 180,000 tons in the 1990s.
  • the cumulative catches of Japan and South Korea have ranged from 100,000 to 200,000 tons.
  • the winter community of Pacific pleated soft squid is mainly based on fishing in Japan and South Korea, and the operations mainly include fishing, bottom towing, fixed nets, and purse seine.
  • the main fishing grounds start from Joban in July to the Pacific coast of Sanriku. From September to November, they move to the Pacific coast of Hokkaido. After November, the main fishing grounds move to the side of the Sea of Japan. The fishing season ends (December to February). )
  • the fishing ground is in the northwestern waters of Kyushu.
  • the catch of the winter life group reached its peak in the 1950s and 1960s.
  • the main fishing ground is in the Pacific Ocean in eastern Hokkaido. In 1968, the catch was 560,000 tons, which accounted for 84% of the catch of Pacific pleated fish in Japan. After that, the catch fell sharply and reached its lowest level in the 1980s. After 1989, the catch has rebounded, reaching 380,000 tons in 1996. Since then, the catch has been changing significantly. At present, the catch is between 200,000 and 300,000 tons.
  • the purpose of the present invention is to overcome the problems and deficiencies of the prior art, and to provide a method for predicting the abundance of Japanese squid resources based on the Pacific Oscillation Index and its application.
  • the present invention provides the following technical solutions:
  • the method for predicting the abundance of Japanese squid resources based on the Pacific Shock Index is applied to electronic equipment to guide the ocean fishing of Japanese squid.
  • the steps are as follows:
  • the correlation analysis of the CPUE of Japanese squid resource abundance and the monthly PDO value of the previous N years is carried out, and the monthly PDO values that are statistically significant correlation are selected, and the monthly PDO values are selected
  • the selected monthly PDO values are numbered in the order of 1 , 2 , 3 ... z ... m, and these monthly PDO values are sequentially recorded as x 1 , x 2 , and x 3 ... X z ... x m , where m is the number of monthly PDO values selected;
  • CPUE is the daily output of small and medium squid fishing boats in Japan
  • a is a constant
  • b n are corresponding to x 1 , x 2 , x 3 ... x z ... x coefficient of m ;
  • the maximum number of Japanese squid resource abundance prediction models is calculated based on the following logic. For a climate factor, there are Models, for the two climate factors, there are Models, and so on, for z climate factors, there are Models, for m climate factors, there are Models, and then add the number of models to get
  • the method for predicting the abundance of Japanese squid resources based on the Pacific Oscillation Index of the present invention establishes for the first time the relationship between the prediction of the climate factor ( Pacific Oscillation Index) and the abundance of Japanese squid resources.
  • the rapid and accurate prediction of the abundance of squid resources can play a good guiding role in marine fishery production (fishing of Japanese squid in autumn / winter), can significantly improve fishing efficiency, reduce fishing costs, and have great application prospects.
  • the optimal model obtained by the present invention is not static, and the optimal model can be obtained again according to the latest data acquired in real time.
  • the method of the present invention has good adaptability and good application prospects.
  • the prediction method for the abundance of Japanese squid based on the Pacific Shock Index after obtaining the optimal model, obtain the corresponding x 1 , x 2 , x 3 ... x z ... x m corresponding to the optimal model, and input it Optimal model, the optimal model output Japanese abundance of squid resources is completed to predict the abundance of Japanese squid resources.
  • the prediction method for the abundance of Japanese squid resources based on the Pacific Oscillation Index.
  • the Japanese squid prediction model is established for a climatic factor x z , then b 1 , b 2 , b 3 , ... b z-1 , b z + 1 , ..., b n are all 0, and so on, and so on, if the Japanese squid resource abundance prediction model is established for the climate factors x 1 and x z , then b 2 , b 3 , ... b z-1 , b z + 1 , ..., b n are all 0.
  • the statistically significant correlation means that the calculated P value is ⁇ 0.05.
  • the P value is a parameter statistically used to determine the hypothesis test result.
  • the P value (P value) is the probability that the sample observation result or the extreme result obtained when the original false is set to true. If the P value is small, the probability of the null hypothesis situation is very small, and if it occurs, according to the principle of small probability, there is a reason to reject the null hypothesis. The smaller the P value, the more reason we reject the null hypothesis. In short, the smaller the P value, the more significant the results.
  • the sea area where squid is distributed in the Japanese autumn group is the sea area of Japan;
  • the sea area where squid is distributed in the Japanese winter group is the Pacific Ocean area of Hokkaido.
  • step (2) two statistically significant monthly PDO values were selected, which were the October PDO value of the previous 2 years and the October PDO value of the previous year.
  • the correlation with the PDO value of October in the previous 2 years was significant, showing a negative correlation, and the correlation coefficient was -0.390 (P ⁇ 0.05).
  • the CPUE of the squid resource abundance in the Japanese autumn group was significantly correlated with the October PDO value in the previous year. It showed a negative correlation with a correlation coefficient of -0.4486 (P ⁇ 0.05);
  • the correlation between the CPUE of Japanese squid resource abundance and the PDO value of each month of the same year is not significant.
  • the number of prediction models mentioned here and below is only a part of the data to demonstrate the operation logic of the prediction method of the present invention. The scope of protection of the present invention is not limited to this. Those skilled in the art can select appropriate data pairs according to actual needs. To predict the abundance of squid resources in Japan, the number of statistically significant monthly PDO values selected is not limited to two, and the number of prediction models will also vary with the number of statistically significant monthly PDO values selected And change.
  • the prediction method for the abundance of Japanese squid based on the Pacific Shock Index has established three prediction models in step (3).
  • the prediction models are as follows:
  • the prediction model I is selected as the optimal model, and the optimal model is:
  • step (2) ten statistically significant monthly PDO values were selected, which were the PDO values of October, November and December of the previous 2 years, and the PDO values of 1, 2, 3 and April of the previous year And the PDO values in January, February, March and April of the same year;
  • the CPUE of the squid resource abundance in the Japanese winter squid was significantly correlated with the PDO values in January, February, March and April of the previous year, showing a negative correlation.
  • the correlation coefficients were -0.4665 (P ⁇ 0.05) and -0.4365 (P ⁇ 0.05), -0.4295 (P ⁇ 0.05) and -0.5072 (P ⁇ 0.01);
  • the prediction method of the Japanese squid resource abundance based on the Pacific Shock Index has established five prediction models in step (3).
  • the prediction models are as follows:
  • the November PDO value x 21 for the first 2 years, the December PDO value x 22 for the previous 2 years, the February PDO value x 23 for the same year, the March PDO value x 24 for the same year, and the March PDO for the previous year Value x 25 to establish a prediction model of squid resource abundance in the Qiusheng group in the Japanese Sea, specifically:
  • the prediction model 2 is selected as the optimal model, and the optimal model is:
  • the invention also provides an electronic device, including one or more processors, one or more memories, one or more programs, and a data collection device;
  • the data collection device is used to obtain x 1 , x 2 , x 3 ... x z ... x m corresponding to the optimal model, the one or more programs are stored in the memory, when the one or more When the program is executed by the processor, the electronic device is caused to perform the method for predicting the abundance of Japanese squid resources based on the Pacific Oscillation Index as described above.
  • the method for predicting the abundance of Japanese squid based on the Pacific Oscillation Index of the present invention uses the Pacific Oscillation Index PDO to realize the prediction of the abundance of Japanese squid resources, which can play a good role in marine fishery production (fishing of Japanese squid)
  • the guiding role can significantly improve fishing efficiency, reduce fishing costs, and has great application prospects;
  • the optimal method of the Japanese squid resource abundance prediction method based on the Pacific Shock Index of the present invention is not static, and the optimal model can be re-acquired based on the latest data obtained in real time.
  • the method of the present invention has good adaptability and application prospects it is good;
  • the electronic device of the present invention has a simple structure and low cost, can quickly realize the prediction of the abundance of Japanese squid resources based on the Pacific Oscillation Index PDO, and has great application prospects.
  • 1 is a flowchart of a method for predicting the abundance of Japanese squid resources based on the Pacific Oscillation Index of the present invention
  • Figure 2 is a graph of CPUE annual abundance changes of squid resource abundance in Japanese autumn groups from 1990 to 2016;
  • Figure 3 is the distribution map of the CPUE actual value and predicted value of the squid resource abundance in the Japanese sea autumn group from 1990 to 2016;
  • Figure 4 is a schematic diagram of the CPUE annual abundance change of the squid resource abundance of Japanese winter squid from 1992 to 2016;
  • Figure 5 is the distribution map of the actual value and the predicted value of CPUE of the abundance of squid in the Japanese sea winter group from 1992 to 2016;
  • FIG. 6 is a schematic structural diagram of an electronic device of the present invention.
  • a method for predicting the abundance of Japanese squid resources based on the Pacific Oscillation Index is used to guide the offshore fishing of Japanese squid, which includes the following steps:
  • Step 101 Obtain the monthly Pacific Oscillation Index PDO value of the sea area where the Japanese squid is distributed in the previous N years.
  • the Japanese squid is the Japanese autumn squid or the Japanese winter squid, and the Japanese autumn squid is the Japanese sea.
  • the Japanese winter The sea area where the squid is distributed is the Pacific side of Hokkaido;
  • Step 102 Using a time series analysis method, perform a correlation analysis between the CPUE of Japanese squid resource abundance and the monthly PDO value of the previous N years, and select the monthly PDO values that are statistically significant correlation among them, and select the monthly PDO values of these months
  • the selected monthly PDO values are numbered in the order of 1 , 2 , 3 ... z ... m, and these monthly PDO values are sequentially recorded as x 1 , x 2 , and x 3 ... X z ... x m , where m is the number of monthly PDO values selected;
  • Step 103 Use multivariate linear equations to establish up to 2 m -1 prediction models of abundance of Japanese squid resources for any 1 to m climate factors in x 1 , x 2 , x 3 ... x m , and calculate the statistics of each prediction model The value of P on the formula, where the formula for the Japanese squid resource abundance prediction model is as follows:
  • CPUE a + b 1 * x 1 + b 2 * x 2 + b 3 * x 3 + ... + b z * x z + ... + b m * x m ;
  • CPUE is the daily output of small and medium squid fishing boats in Japan
  • a is a constant
  • b n are corresponding to x 1 , x 2 , x 3 ... x z ... x coefficient of m ;
  • Step 104 Among the above 2 m -1 Japanese squid resource abundance prediction models, select the model with the smallest statistical P value as the optimal model;
  • Step 105 Obtain x 1 , x 2 , x 3 ... x z ... x m corresponding to the optimal model, and input it into the optimal model, and output the optimal model to the abundance of Japanese squid resources. Degree of prediction.
  • the Pacific Oscillation Index is a phenomenon of Pacific climate change that changes on a 10-year cycle scale. The conversion period is usually 20 to 30 years.
  • the PDO is characterized by an abnormally warm or cold surface seawater temperature in the area north of 20 degrees north latitude of the Pacific Ocean. During the "warm phase” (or “positive phase") of the 10-year Pacific Oscillation, the western Pacific is colder and the eastern Pacific is warmer.
  • the Japanese abundance squid resource abundance index CPUE (in tons per ship) comes from the production of small and medium-sized squid fishing vessels in Japan from 1990 to 2016 (Table 2).
  • the CPUE of the squid resource abundance in the Japanese squid group was correlated with the PDO value from January to December 1988-2016 Analysis, select monthly PDO values that are statistically significant (P value ⁇ 0.05), and use these monthly PDO values as the climatic factors that affect the abundance of squid resources in the Japanese autumn group, according to 1, 2, 3 ... z ... M sequentially number the selected monthly PDO values, and record these monthly PDO values as x 1 , x 2 , x 3 ... x z ... x m , m is the number of selected monthly PDO values;
  • CPUE a + b 1 * x 1 + b 2 * x 2 + b 3 * x 3 + ... + b z * x z + ... + b m * x m ;
  • CPUE is the daily output of a single ship
  • a is a constant
  • b n are coefficients corresponding to x 1 , x 2 , x 3 ... x z ... x m , respectively;
  • the change trend of resource abundance between the actual value and the predicted value is shown in FIG. 3, as can be seen from FIG. 3, the change trend of the predicted value and the actual value is basically the same, that is, the method of the present invention can effectively The abundance of squid resources is predicted.
  • the Pacific Oscillation Index is a phenomenon of Pacific climate change that changes on a 10-year cycle scale. The conversion period is usually 20 to 30 years.
  • the PDO is characterized by an abnormally warm or cold surface seawater temperature in the area north of 20 degrees north latitude of the Pacific Ocean. During the "warm phase” (or “positive phase") of the 10-year Pacific Oscillation, the western Pacific is colder and the eastern Pacific is warmer.
  • the Japanese winter squid resource abundance index CPUE (in tons per ship) comes from the production of small and medium-sized squid fishing boats in Japan from 1992 to 2016 (Table 7).
  • CPUE a + b 1 * x 1 + b 2 * x 2 + b 3 * x 3 + ... + b z * x z + ... + b m * x m ;
  • CPUE is the daily output of a single ship
  • a is a constant
  • b n are coefficients corresponding to x 1 , x 2 , x 3 ... x z ... x m , respectively;
  • the optimal model outputs the abundance of squid resources of the Japanese winter live group. Forecast of squid resources.
  • the correlation analysis of the resource abundance CPUE and the PDO value of each month of the previous 2 years believes that its resource abundance CPUE has a significant correlation with the PDO value of October-December of the previous 2 years, and has a negative correlation, and the correlation coefficients are- 0.4506 (P ⁇ 0.05), -0.4985 (P ⁇ 0.05), -0.5878 (P ⁇ 0.01);
  • the correlation analysis of the resource abundance CPUE and the PDO value of each month of the previous year believes that the resource abundance CPUE has a significant correlation with the PDO value of January-April of the previous year and has a negative correlation, and the correlation coefficients are -0.4665 (P ⁇ 0.05), -0.4365 (P ⁇ 0.05), -0.4295 (P ⁇ 0.05), -0.5072 (P ⁇ 0.01);
  • the correlation analysis between the resource abundance CPUE and the PDO value of each month of the same year believes that the resource abundance CPUE has a significant correlation with the PDO value from January to April of the same year, and shows a negative correlation, and the correlation coefficients are -0.4746 (P ⁇ 0.05), -0.4837 (P ⁇ 0.05), -0.5458 (P ⁇ 0.01), -0.5570 (P ⁇ 0.01).
  • the November PDO value x 21 for the first 2 years, the December PDO value x 22 for the previous 2 years, the February PDO value x 23 for the same year, the March PDO value x 24 for the same year, and the March PDO for the previous year Value x 25 to establish a prediction model of squid resource abundance in the Qiusheng group in the Japanese Sea, specifically:
  • An electronic device includes one or more processors, one or more memories, one or more programs, and data collection devices;
  • the data collection device is used to obtain x 1 , x 2 , x 3 ... x z ... x m corresponding to the optimal model, one or more programs are stored in the memory, when one or more programs are executed by the processor, so that The electronic device executes the method for predicting the abundance of Japanese squid resources based on the Pacific Oscillation Index as described in Example 1 or Example 2.

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Abstract

La présente invention concerne un procédé de prédiction d'abondance des ressources en toutenons japonais (Todarodes pacificus) basé sur l'oscillation décennale du Pacifique. Le procédé comprend les étapes consistant à : acquérir des valeurs d'oscillation décennale du Pacifique (ODP) mensuelles des zones marines où le toutenon japonais a été réparti durant les N dernières années ; à l'aide d'un procédé d'analyse de séquence temporelle pour effectuer une analyse de corrélation sur une capture par unité d'effort (CPUE) de l'abondance des ressources en toutenons japonais et les valeurs d'ODP mensuelles des N dernières années, sélectionner les valeurs d'ODP mensuelles qui sont associées statistiquement de manière significative, numéroter dans l'ordre ces valeurs d'ODP mensuelles sélectionnées, et marquer celles-ci dans l'ordre comme x1, x2, x3...xz...xm ; établir au plus 2m-1 modèles de prédiction d'abondance des ressources en toutenons japonais pour n'importe lequel des m facteurs climatiques à l'aide d'une équation linéaire à variables multiples, et calculer une valeur P de chaque modèle de prédiction ; et sélectionner un modèle ayant la valeur P minimale en tant que modèle optimal. Dans le procédé, des valeurs d'oscillation décennale du Pacifique (ODP) sont utilisées pour réaliser une prédiction d'abondance des ressources en toutenons japonais, qui a une fonction de guidage pour la production halieutique, améliore l'efficacité de la pêche, réduit les coûts de pêche et présente de bonnes perspectives d'application.
PCT/CN2019/114867 2018-11-02 2019-10-31 Procédé de prédiction d'abondance des ressources en toutenons japonais (todarodes pacificus) et application basée sur l'oscillation décennale du pacifique WO2020088615A1 (fr)

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CN201811300078.X 2018-11-02
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CN201811300078.XA CN109523070A (zh) 2018-11-02 2018-11-02 基于太平洋震荡指数的日本冬生群鱿鱼资源丰度预测方法
CN201811299884.XA CN109472405A (zh) 2018-11-02 2018-11-02 基于太平洋震荡指数的日本秋生群鱿鱼资源丰度预测方法

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