CN109523058A - Peru squid stock number medium- and long-term forecasting method based on ocean Nino index - Google Patents
Peru squid stock number medium- and long-term forecasting method based on ocean Nino index Download PDFInfo
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- 241000238366 Cephalopoda Species 0.000 title claims abstract description 73
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Abstract
A kind of Peru squid stock number medium- and long-term forecasting method based on ocean Nino index of the present invention, comprising: the ocean Nino index ONI value monthly in the Eastern Pacific sea area of N Peru squid distribution before obtaining；Utilize Time series analysis method, correlation analysis is carried out to the ONI value of Peru squid resource abundance ln (CPUE) and preceding N monthly, the moon ONI value of statistically relevant P < 0.05 is obtained, those month ONI value is as the climatic factor for influencing Peru squid resource abundance；P value on multiple Peru squid resource abundance prediction models and counting statistics, formula: ln (CPUE)=a+b1*x1+b2*x2+b3*x3+ ...+bn*xn are established using multiple linear equation；In above-mentioned multiple Peru's resource abundance prediction models, select statistically the smallest model of P value as optimal models.
Description
Technical field
The present invention relates to squid Resources Prediction technical fields, more particularly to a kind of Peru based on ocean Nino index
Squid stock number medium- and long-term forecasting method.
Background technique
Peru squid has been economic Resources of Cephalopods important in the world since 2000, the maximum output of 2016-2017
It is that the oceanic fishing countrys such as the coastal states such as Peru, Chile, Mexico and China and the main of area are caught more than 1,000,000 tons
Object is fished out, fishing ground is widely distributed in southeast Pacific sea area.Peru squid is mainly distributed on Eastern Pacific sea area, by Peru
The influence of upper up-flow caused by ocean current.Existing research shows that resource is mended since Peru squid is the type of short life cycle
Charge is influenced by marine environment.Wang Jintao etc. (2014) is according to the China 2003-2012 squid jigging boat in southeast Pacific
The sea surface temperature (SST) of production statistics data and jumbo flying squid habitat, sea level height (SSH), chlorophyll-a concentration (chl-a)
Data, using correlation analysis analyze jumbo flying squid resource abundance and magnitude of recruitment (using catch per unit effort as index,
T/d) with the correlation for SST, SSH, chl-a concentration for inhabiting the S-20 ° of N in 20 ° of sea area, 110 ° of W-70 ° of W, it is big to obtain related coefficient
Crucial sea area position, while be added the most suitable surface temperature range in jumbo flying squid spawning ground, feeding ground account for the gross area ratio (respectively
Indicated with PS, PF) two parameters, establish three kinds of error back propagation (EBP) neural network resources based on the main environment factor
Magnitude of recruitment forecasting model.Xu Bing etc. (2013) according to the China 2003-2010 squid jigging boat waters off Peru production statistics data
Sea surface temperature (SST) data obtained with remote sensing, the resource abundance and benefit of jumbo flying squid are analyzed using canonical correlation analysis method
Correlation charge (using catch per unit effort as index) and inhabit each fishing zone SST in sea area, obtaining influences outside Peru
The SST factor of extra large jumbo flying squid resource abundance and magnitude of recruitment, and establish the resource abundance prediction model based on SST.The studies above table
Bright, current each scholar both at home and abroad influences its resource magnitude of recruitment to Peru squid spawning ground and feeding ground environment and grind well
Study carefully, and establish corresponding Resources Prediction model, but is then empty how to carry out look-ahead its stock number with climatic factor
It is white.
Summary of the invention
The present invention is in view of the problems of the existing technology and insufficient, provides a kind of Peru squid based on ocean Nino index
Stock number medium- and long-term forecasting method.
The present invention is to solve above-mentioned technical problem by following technical proposals:
The present invention provides a kind of Peru squid stock number medium- and long-term forecasting method based on ocean Nino index, and feature exists
In comprising following steps:
The ocean Nino index ONI value monthly in the Eastern Pacific sea area that N Peru squid is distributed before S1, acquisition；
S2, using Time series analysis method, to Peru squid resource abundance ln (CPUE) and the ONI value of preceding N monthly
Correlation analysis is carried out, obtains the moon ONI value of statistically relevant P < 0.05, those month ONI value is as influence Peru squid
The climatic factor of resource abundance；
S3, P value on multiple Peru squid resource abundance prediction models and counting statistics is established using multiple linear equation,
Formula are as follows: ln (CPUE)=a+b1*x1+b2*x2+b3*x3+ ...+bn*xn, in formula, CPUE is single ship annual output, and a is normal
Number, b1, b2, b3 ..., bn be equation coefficient；X1, x2, x3 ..., xn be influence resource abundance moon ONI value；
S4, in above-mentioned multiple Peru's resource abundance prediction models, select statistically the smallest model of P value as optimal mould
Type.
On the basis of common knowledge of the art, above-mentioned each optimum condition, can any combination to get each preferable reality of the present invention
Example.
The positive effect of the present invention is that:
(1) prediction of Peru squid resource abundance is carried out using ocean Nino index ONI；
(2) select preceding in June, 2, July and August ONI value as the climatic prediction factor；
(3) Peru squid resource abundance prediction model are as follows: Ln (CPUE)=7.1311-0.4428*ONIT-2,6+1.6145*
ONIT-2,7-0.8598*ONIT-2,8, ONIT-2,6、ONIT-2,7、ONIT-2,8It is in June, 2, July and 8 respectively before the Nino index of ocean
The ONI value of the moon.
Detailed description of the invention
Fig. 1 is the flow chart of the Peru squid stock number medium- and long-term forecasting method based on ocean Nino index.
Fig. 2 is the schematic diagram that 2001-2016 Peru squid resource abundance ln (CPUE) changes between year.
Fig. 3 is 2001-2016 Peru squid resource abundance ln (CPUE) actual value and predicted value change profile figure.
Specific embodiment
In order to make the object, technical scheme and advantages of the embodiment of the invention clearer, below in conjunction with the embodiment of the present invention
In attached drawing, technical scheme in the embodiment of the invention is clearly and completely described, it is clear that described embodiment is
A part of the embodiment of the present invention, instead of all the embodiments.Based on the embodiments of the present invention, those of ordinary skill in the art
Every other embodiment obtained without making creative work, shall fall within the protection scope of the present invention.
As shown in Figure 1, the present invention provides a kind of Peru squid stock number medium- and long-term forecasting side based on ocean Nino index
Method comprising following steps:
Step 101, the ocean Nino index ONI value monthly for obtaining the Eastern Pacific sea area that preceding N Peru squid is distributed.
Step 102, using Time series analysis method, to Peru squid resource abundance ln (CPUE) and preceding N monthly
ONI value carries out correlation analysis, obtains statistically significant relevant moon ONI value, those month ONI value is as influence Peru squid
The climatic factor of resource abundance.
Step 103 establishes P on multiple Peru squid resource abundance prediction models and counting statistics using multiple linear equation
Value, formula are as follows: ln (CPUE)=a+b1*x1+b2*x2+b3*x3+ ...+bn*xn, in formula, CPUE is single ship annual output, a
For constant, b1, b2, b3 ..., the coefficient that bn is equation；X1, x2, x3 ..., xn be influence resource abundance moon ONI value.
Step 104, in above-mentioned multiple Peru's resource abundance prediction models, select statistically the smallest model of P value as
Optimal models.
A specific example is named to illustrate the present invention, so that those skilled in the art better understood when this
The technical solution of invention.
1, material and method
(1) data source
Peru squid is distributed in the sea area of Eastern Pacific, which is influenced by EI Nino, spawning ground and forage
Field is influenced by rising intensity of flow caused by peru current.In the sea area, EI Nino (El) it is an important gas
The factor is waited, EI Nino event refers in equator, the phenomenon that the Eastern Pacific sea a wide range of persistent anomaly of table is partially warm, judgment criteria
There is also certain differences in the world.3 area's sea surface temperature anomalies index of NINO is generally reached 0.5 DEG C defined above as in continuous 6 months
EI Nino event, the U.S. then by 3 months sliding averages of 3.4 area's sea surface temperature anomalies of NINO reach 0.5 DEG C it is defined above
For an EI Nino event.More fully to reflect in equator, the integral status of Eastern Pacific, country, China Meteorological Administration gas
Time center is in business mainly using the sea surface temperature anomalies index in the complex zone NINO (area NINO 1+2+3+4) as judgement EI Nino
The foundation of event, index are as follows: the complex zone NINO sea surface temperature anomalies index continues 6 months or more >=0.5 DEG C as an EI Nino
Event；If area's index continues 5 months >=0.5 DEG C, and the sum of 5 months index >=4.0 DEG C, it is also defined as an EI Nino
Event.
Ocean Nino index OceanicThe http of Index (ONI) from American National climatic prediction center: //
Origin.cpc.ncep.noaa.gov/products/analysis_monitoring/en sostuff/ONI_v5.php) net
It stands, time period is in January, 1999 in December, 2017 (table 1).ONI is continuous trimestral average value.
Peru squid Resources Richness Rate Index (CPUE unit be ton/ship) is from Chinese ocean squid jigging boat annual output, time
- 2017 years 2001 (table 2).
Table in December, -2017 in January, 1 2000 ocean Nino index (ONI) monthly returns
| Time | January | 2 months | March | April | May | June | July | August | September | October | November | December |
| 1999 | -1.5 | -1.3 | -1.1 | -1.0 | -1.0 | -1.0 | -1.1 | -1.1 | -1.2 | -1.3 | -1.5 | -1.7 |
| 2000 | -1.7 | -1.4 | -1.1 | -0.8 | -0.7 | -0.6 | -0.6 | -0.5 | -0.5 | -0.6 | -0.7 | -0.7 |
| 2001 | -0.7 | -0.5 | -0.4 | -0.3 | -0.3 | -0.1 | -0.1 | -0.1 | -0.2 | -0.3 | -0.3 | -0.3 |
| 2002 | -0.1 | 0.0 | 0.1 | 0.2 | 0.4 | 0.7 | 0.8 | 0.9 | 1.0 | 1.2 | 1.3 | 1.1 |
| 2003 | 0.9 | 0.6 | 0.4 | 0.0 | -0.3 | -0.2 | 0.1 | 0.2 | 0.3 | 0.3 | 0.4 | 0.4 |
| 2004 | 0.4 | 0.3 | 0.2 | 0.2 | 0.2 | 0.3 | 0.5 | 0.6 | 0.7 | 0.7 | 0.7 | 0.7 |
| 2005 | 0.6 | 0.6 | 0.4 | 0.4 | 0.3 | 0.1 | -0.1 | -0.1 | -0.1 | -0.3 | -0.6 | -0.8 |
| 2006 | -0.8 | -0.7 | -0.5 | -0.3 | 0.0 | 0.0 | 0.1 | 0.3 | 0.5 | 0.7 | 0.9 | 0.9 |
| 2007 | 0.7 | 0.3 | 0.0 | -0.2 | -0.3 | -0.4 | -0.5 | -0.8 | -1.1 | -1.4 | -1.5 | -1.6 |
| 2008 | -1.6 | -1.4 | -1.2 | -0.9 | -0.8 | -0.5 | -0.4 | -0.3 | -0.3 | -0.4 | -0.6 | -0.7 |
| 2009 | -0.8 | -0.7 | -0.5 | -0.2 | 0.1 | 0.4 | 0.5 | 0.5 | 0.7 | 1.0 | 1.3 | 1.6 |
| 2010 | 1.5 | 1.3 | 0.9 | 0.4 | -0.1 | -0.6 | -1.0 | -1.4 | -1.6 | -1.7 | -1.7 | -1.6 |
| 2011 | -1.4 | -1.1 | -0.8 | -0.6 | -0.5 | -0.4 | -0.5 | -0.7 | -0.9 | -1.1 | -1.1 | -1.0 |
| 2012 | -0.8 | -0.6 | -0.5 | -0.4 | -0.2 | 0.1 | 0.3 | 0.3 | 0.3 | 0.2 | 0.0 | -0.2 |
| 2013 | -0.4 | -0.3 | -0.2 | -0.2 | -0.3 | -0.3 | -0.4 | -0.4 | -0.3 | -0.2 | -0.2 | -0.3 |
| 2014 | -0.4 | -0.4 | -0.2 | 0.1 | 0.3 | 0.2 | 0.1 | 0.0 | 0.2 | 0.4 | 0.6 | 0.7 |
| 2015 | 0.6 | 0.6 | 0.6 | 0.8 | 1.0 | 1.2 | 1.5 | 1.8 | 2.1 | 2.4 | 2.5 | 2.6 |
| 2016 | 2.5 | 2.2 | 1.7 | 1.0 | 0.5 | 0.0 | -0.3 | -0.6 | -0.7 | -0.7 | -0.7 | -0.6 |
| 2017 | -0.3 | -0.1 | 0.1 | 0.3 | 0.4 | 0.4 | 0.2 | -0.1 | -0.4 | -0.7 | -0.9 | -1.0 |
The Chinese squid jigging boat annual output of 2 2001-2016 of table
(2) research method and step
Since Peru squid resource abundance is using squid jigging boat annual yield as index, the index is because of the factors meeting such as production statistics
Error is generated, therefore to its Resources Richness Rate Index by taking natural logrithm ln (CPUE) to be standardized.
Using Time series analysis method, correlation is carried out to ln (CPUE) value and the ONI value of the 1999-2016 1-12 month
Analysis, obtains statistically relevant moon ONI value (statistically P < 0.05), the ONI value of these months is provided as Peru squid is influenced
The climatic factor of source abundance.
Multiple Peru squid resource abundance prediction models, formula are established using multiple linear equation are as follows: ln (CPUE)=a
+b1*x1+b2*x2+b3*x3+……+bn*xn.In formula, CPUE is single ship annual output, and a is constant, b1, b2, b3 ..., bn
For the coefficient of equation；X1, x2, x3 ..., xn be influence resource abundance moon ONI value.It is pre- in above-mentioned multiple Peru's resource abundances
Survey model in, select statistically the smallest model of P value as optimal models.
2, result of study
(1) resource abundance ln (CPUE) changes between year
As shown in Figure 2, Peru squid resource abundance ln (CPUE) changes between significant year is presented, 2004,2008,
It is horizontal to be within 2010,2014 high stock number；And 2001,2005,2012 and 2016 are then in low resource
Amount is horizontal.
(2) the ONI value of resource abundance ln (CPUE) is influenced
Resource abundance ln (CPUE) and the correlation analysis of the ONI value of preceding 2 years each moons think, resource abundance ln (CPUE)
It is significant (P < 0.05) with first 2 years 6-11 month ONI value correlations, it presents and is positively correlated, related coefficient is respectively 0.5512,
0.5913、0.6199、0.5776、0.5431、0.5066。
Resource abundance ln (CPUE) and the correlation analysis of the ONI value of preceding 1 year each moon think, resource abundance ln (CPUE)
1-12 month ONI value correlation with first 1 year is not significant (P ﹥ 0.05).
(3) model of resource abundance prediction is established
1) one of prediction model
2 years in the past 6-7 months ONI value (ONIT-2,6, ONIT-2,7) it is used as predictive factor, establish Peru squid resource abundance
Prediction model are as follows:
Ln (CPUE)=7.1018-0.08599*ONIT-2,6+0.32998*ONIT-2,7
Its F value is 0.5931 (P=0.0597 ﹥ 0.05).
The statistical form of its actual value and predicted value such as table 3.
3 Peru squid resource abundance actual value of table and predicted value and its residual error
2) the two of prediction model
2 years in the past 6-8 months ONI value (ONIT-2,6, ONIT-2,7, ONIT-2,8) it is used as predictive factor, establish Peru squid money
Source abundance prediction model are as follows:
Ln (CPUE)=7.1102+0.22578*ONIT-2,6-0.45788*ONIT-2,7+0.47278*ONIT-2,8
Its F value is 2.6388 (P=0.097 ﹥ 0.05).
The statistical form of its actual value and predicted value such as table 4.
4 Peru squid resource abundance actual value of table and predicted value and its residual error
3) the three of prediction model
2 years in the past 6-9 months ONI value (ONIT-2,6, ONIT-2,7, ONIT-2,8, ONIT-2,9) it is used as predictive factor, it establishes secret
Shandong squid resource abundance prediction model are as follows:
Ln (CPUE)=7.1558+0.5804*ONIT-2,6-1.367*ONIT-2,7+2.2949*ONIT-2,8-1.0906*
ONIT-2,9
Its F value is 3.370 (P=0.049 < 0.05).
The statistical form of its actual value and predicted value such as table 5.
5 Peru squid resource abundance actual value of table and predicted value and its residual error
4) the four of prediction model
2 years in the past 6-10 months ONI value (ONIT-2,6, ONIT-2,7, ONIT-2,8, ONIT-2,9, ONIT-2,10) as prediction because
Son establishes Peru squid resource abundance prediction model are as follows:
Ln (CPUE)=7.1748+0.5647*ONIT-2,6-1.5945*ONIT-2,7+3.2863*ONIT-2,8-2.4778*
ONIT-2,9+0.6242*ONIT-2,10
Its F value is 2.852 (P=0.074 ﹥ 0.05).
The statistical form of its actual value and predicted value such as table 6.
6 Peru squid resource abundance actual value of table and predicted value and its residual error
5) the five of prediction model
2 years in the past 6-11 months ONI value (ONIT-2,6, ONIT-2,7, ONIT-2,8, ONIT-2,9, ONIT-2,10, ONIT-2,11) make
For predictive factor, Peru squid resource abundance prediction model is established are as follows:
Ln (CPUE)=7.1748+0.5478*ONIT-2,6-1.5539*ONIT-2,7+3.2762*ONIT-2,8-2.5456*
ONIT-2,9+0.7257*ONIT-2,10-0.0478*ONIT-2,11
Its F value is 2.1411 (P=0.1465 ﹥ 0.05).
The statistical form of its actual value and predicted value such as table 7.
7 Peru squid resource abundance actual value of table and predicted value and its residual error
6) the six of prediction model
2 years in the past 7-9 months ONI value (ONIT-2,7, ONIT-2,8, ONIT-2,9) it is used as predictive factor, establish Peru squid money
Source abundance prediction model are as follows:
Ln (CPUE)=7.1311-0.4428*ONIT-2,7+1.6145*ONIT-2,8-0.8598*ONIT-2,9
Its F value is 3.962 (P=0.0355 < 0.05).
The statistical form of its actual value and predicted value such as table 8.
8 Peru squid resource abundance actual value of table and predicted value and its residual error
By above-mentioned six model comparative analysis it can be concluded that, this research select preceding in June, 2, July, August ONI value as
The climatic prediction factor, Peru squid resource abundance prediction model are as follows: Ln (CPUE)=7.1311-0.4428*ONIT-2,7+
1.6145*ONIT-2,8-0.8598*ONIT-2,9.The resource abundance variation tendency of its actual value and predicted value is as shown in Figure 3.
Although specific embodiments of the present invention have been described above, it will be appreciated by those of skill in the art that these
It is merely illustrative of, protection scope of the present invention is defined by the appended claims.Those skilled in the art is not carrying on the back
Under the premise of from the principle and substance of the present invention, many changes and modifications may be made, but these are changed
Protection scope of the present invention is each fallen with modification.
Claims (4)
1. a kind of Peru squid stock number medium- and long-term forecasting method based on ocean Nino index, which is characterized in that it include with
Lower step:
The ocean Nino index ONI value monthly in the Eastern Pacific sea area that N Peru squid is distributed before S1, acquisition；
S2, using Time series analysis method, to the ONI value progress of Peru squid resource abundance ln (CPUE) and preceding N monthly
Correlation analysis obtains the moon ONI value of statistically relevant P < 0.05, those month ONI value is as influence Peru squid resource
The climatic factor of abundance；
S3, P value on multiple Peru squid resource abundance prediction models and counting statistics, formula are established using multiple linear equation
Are as follows: ln (CPUE)=a+b1*x1+b2*x2+b3*x3+ ...+bn*xn, in formula, CPUE is single ship annual output, and a is constant, b1,
B2, b3 ..., bn be equation coefficient；X1, x2, x3 ..., xn be influence resource abundance moon ONI value；
S4, in above-mentioned multiple Peru's resource abundance prediction models, select statistically the smallest model of P value as optimal models.
2. the Peru squid stock number medium- and long-term forecasting method based on ocean Nino index as described in claim 1, feature
It is, it is in step s 2, secret according to the correlation analysis of Peru squid resource abundance ln (CPUE) and the ONI value of preceding 2 years each moons
Shandong squid resource abundance ln (CPUE) is significant (P < 0.05) with first 2 years 6-11 month ONI value correlations, presents and is positively correlated, phase
Relationship number is respectively 0.5512,0.5913,0.6199,0.5776,0.5431,0.5066；
According to the correlation analysis of Peru squid resource abundance ln (CPUE) and the ONI value of preceding 1 year each moon, Peru squid resource is rich
The 1-12 month ONI value correlation for spending ln (CPUE) with first 1 year is not significant (P ﹥ 0.05).
3. the Peru squid stock number medium- and long-term forecasting method based on ocean Nino index as claimed in claim 2, feature
It is, in step s3,
1) one of prediction model
2 years in the past 6-7 months ONI value (ONIT-2,6, ONIT-2,7) it is used as predictive factor, establish Peru squid resource abundance prediction mould
Type are as follows:
Ln (CPUE)=7.1018-0.08599*ONIT-2,6+0.32998*ONIT-2,7
Its F value is 0.5931, P=0.0597 ﹥ 0.05；
2) the two of prediction model
2 years in the past 6-8 months ONI value (ONIT-2,6, ONIT-2,7, ONIT-2,8) it is used as predictive factor, it is rich to establish Peru squid resource
Spend prediction model are as follows:
Ln (CPUE)=7.1102+0.22578*ONIT-2,6-0.45788*ONIT-2,7+0.47278*ONIT-2,8
Its F value is 2.6388, P=0.097 ﹥ 0.05；
3) the three of prediction model
2 years in the past 6-9 months ONI value (ONIT-2,6, ONIT-2,7, ONIT-2,8, ONIT-2,9) it is used as predictive factor, establish Peru's squid
Fish resource abundance prediction model are as follows:
Ln (CPUE)=7.1558+0.5804*ONIT-2,6-1.367*ONIT-2,7+2.2949*ONIT-2,8-1.0906*ONIT-2,9
Its F value is 3.370, P=0.049 < 0.05；
4) the four of prediction model
2 years in the past 6-10 months ONI value (ONIT-2,6, ONIT-2,7, ONIT-2,8, ONIT-2,9, ONIT-2,10) it is used as predictive factor, it builds
Vertical Peru squid resource abundance prediction model are as follows:
Ln (CPUE)=7.1748+0.5647*ONIT-2,6-1.5945*ONIT-2,7+3.2863*ONIT-2,8-2.4778*ONIT-2,9
+0.6242*ONIT-2,10
Its F value is 2.852, P=0.074 ﹥ 0.05；
5) the five of prediction model
2 years in the past 6-11 months ONI value (ONIT-2,6, ONIT-2,7, ONIT-2,8, ONIT-2,9, ONIT-2,10, ONIT-2,11) as pre-
The factor is surveyed, Peru squid resource abundance prediction model is established are as follows:
Ln (CPUE)=7.1748+0.5478*ONIT-2,6-1.5539*ONIT-2,7+3.2762*ONIT-2,8-2.5456*ONIT-2,9
+0.7257*ONIT-2,10-0.0478*ONIT-2,11
Its F value is 2.1411, P=0.1465 ﹥ 0.05；
6) the six of prediction model
2 years in the past 7-9 months ONI value (ONIT-2,7, ONIT-2,8, ONIT-2,9) it is used as predictive factor, it is rich to establish Peru squid resource
Spend prediction model are as follows:
Ln (CPUE)=7.1311-0.4428*ONIT-2,7+1.6145*ONIT-2,8-0.8598*ONIT-2,9
Its F value is 3.962, P=0.0355 < 0.05.
4. the Peru squid stock number medium- and long-term forecasting method based on ocean Nino index as claimed in claim 3, feature
It is, in step s 4, selects preceding in June, 2, July and August ONI value as the climatic prediction factor；
Peru squid resource abundance prediction model are as follows: Ln (CPUE)=7.1311-0.4428*ONIt-2,6+1.6145*ONIT-2,7-
0.8598*ONIT-2,8, ONIT-2,6、ONIT-2,7、ONIT-2,8It is the ONI in June, 2, July and August respectively before the Nino index of ocean
Value.
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