CN107403243A - Morocco's marine site Resources of Cephalopods abundance Forecasting Methodology - Google Patents
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- 241000238366 Cephalopoda Species 0.000 title claims abstract description 32
- 238000000034 method Methods 0.000 title claims abstract description 10
- 241000238413 Octopus Species 0.000 claims abstract description 53
- PEDCQBHIVMGVHV-UHFFFAOYSA-N Glycerine Chemical compound OCC(O)CO PEDCQBHIVMGVHV-UHFFFAOYSA-N 0.000 claims abstract description 7
- 238000010219 correlation analysis Methods 0.000 claims abstract description 5
- 241000238371 Sepiidae Species 0.000 claims description 7
- 238000012549 training Methods 0.000 claims description 7
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 3
- 230000010355 oscillation Effects 0.000 abstract description 4
- 238000004519 manufacturing process Methods 0.000 description 24
- 238000004458 analytical method Methods 0.000 description 5
- 230000000875 corresponding effect Effects 0.000 description 4
- 238000012545 processing Methods 0.000 description 3
- 241000251468 Actinopterygii Species 0.000 description 2
- 241001125048 Sardina Species 0.000 description 2
- 230000002596 correlated effect Effects 0.000 description 2
- 238000011161 development Methods 0.000 description 2
- 235000019688 fish Nutrition 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 235000019512 sardine Nutrition 0.000 description 2
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- 241001269238 Data Species 0.000 description 1
- 241000287219 Serinus canaria Species 0.000 description 1
- 230000015572 biosynthetic process Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 239000003673 groundwater Substances 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 230000000050 nutritive effect Effects 0.000 description 1
- 230000008092 positive effect Effects 0.000 description 1
- 239000000843 powder Substances 0.000 description 1
- 150000003839 salts Chemical class 0.000 description 1
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Abstract
The present invention discloses a kind of Morocco marine site Resources of Cephalopods abundance Forecasting Methodology, obtains 1,982 2015 years Moroccan fishing data, each moon Arctic oscillation index NAO in the North Atlantic Ocean, 30 ° of 34 ° of N, 8 ° of W, 12 ° of W marine sites SSTA data；Obtain the NAO in corresponding yeariIndex, calculate the average SSTA in the year of 8 ° of 12 ° of W marine sites i-th of each latitude sectioni；6 marine climates and envirment factor are obtained, is respectively：Climatic factor NAOiIndex, envirment factor：SSTA1、SSTA2、SSTA3、SSTA4、SSTA5；Obtain each annual octopus class Resources Richness Rate Index RA1, each annual Resources of Cephalopods abundance combined index RA2；6 marine climates carry out correlation analysis with RA1 and RA2 respectively with envirment factor；Resource abundance forecast model is established using unitary linear model with RA1 and RA2 according to the factor of influence of acquisition respectively.
Description
Technical field
The present invention relates to Resources of Cephalopods abundance electric powder prediction, is provided more particularly to a kind of Morocco marine site siphonopods
Source abundance Forecasting Methodology.
Background technology
Kingdom of Morocco is located at African northwest end, and the Atlantic Ocean is on the point of in west, is the door in the connection Atlantic Ocean, Mediterranean, and Morocco is extra large
The long 2983km of water front, its central Atlantic side are 2446km, and Mediterranean side is 537km, the continental shelf within 200m isobaths
Area is 60,000 km2, continental shelf width is generally 20~30m, and fishing ground water surface area is km more than 1002, with sardine at the middle and upper levels,
The siphonopods product such as octopus of bottom is well-known, is one of rare excellent fishing ground in the world.Wherein cephalopodous yield accounts for
The 15~20% of Morocco's fishery total output, are only second to sardine yield.
Phase early 1970s Morocco's siphonopods Fisheries Development is more slow, and annual production is relatively low, until the eighties
Annual production starts to increase considerably, and 1980 annual productions reach more than 15000t, then increase year by year, the whole year middle and later periods eighties
Yield all maintains 50000t or so, in the 1990s, annual production increases considerably again, the latter stage nineties breaks through to for entrance
More than 100000t, until 2000, annual production highest, close to 150000t, into 21 century after annual production start to reduce,
The annual production of 2003 and 2004 is relatively low, only more than 2000 ton, remaining time annual production 5000t to 10000t it
Between.
In Moroccan fishery output, octopus is main species.According to calendar year statistics data, the 1970s rubs
The octopus development of resources of Lip river brother marine site is in reduced levels, and annual production is relatively low.To the beginning of the eighties, annual production increases substantially,
The average annual productivity of the eighties further gets a promotion in 26000t or so to the nineties, annual production, this period Nei Nianping
Equal yield breaks through 60000t, and octopus annual production at the beginning of 21 century is still in higher level, and subsequent annual production starts to reduce, 2004
Below annual production tumble 20000t, start annual production within 2005 and return to more than 40000t, coming years yield is held at
More than 30000t, and come down to annual production in 2012, only 18000t or so, but carried in 2013 annual productions
Rise, reach more than 50000t.On the whole start to develop at the beginning of the annual production 80 of the octopus in Morocco marine site, by 20th century 90
There is downward trend after the peak period in age.
China begins participating in Morocco's marine site siphonopods fishing operation from phase late 1980s, have accumulated substantial amounts of life
Industry is tested.Due to the species that siphonopods is 1 year, its resource abundance and marine environment are in close relations, and the difference of marine environment is direct
Cephalopodous resource abundance is had influence on, and then has influence on fish production and scientific management.Therefore, selection influences its resource abundance
Envirment factor, to establish resource abundance forecast model particularly important, if it is possible to it is pre- to establish statistically significant resource abundance
Survey model, can scientific guidance in the cephalopodous production in Morocco marine site, it is high to be also that Chinese relevant enterprise is carried out in Morocco marine site
Effect fishing offer science reference.
The content of the invention
The present invention is directed to problem and shortage existing for prior art, there is provided a kind of Morocco marine site Resources of Cephalopods abundance is pre-
Survey method.
The present invention is that solve above-mentioned technical problem by following technical proposals：
The present invention provides a kind of Morocco marine site Resources of Cephalopods abundance Forecasting Methodology, and its feature is that it includes following
Step：
S1, the Moroccan fishing data of 1982-2015 are obtained, obtain each moon north in the 1982-2015 North Atlantic Oceans
Pole Oscillation Index NAO data, and obtain 30 ° of -34 ° of N, 8 ° of W-12 ° of W marine sites table temperature anomaly average SSTA data；
Wherein, the fishing data include cuttlefishes fishery output, octopus class fishery output and siphonopods fishing total yield
Amount；
S2, the NAO data of each each moon in year are averaged to the NAO that year is corresponded to acquisitioniIndex, respectively with
On the basis of 30.5 ° of N, 31.5 ° of N, 32.5 ° of N, 33.5 ° of N and 34.5 ° of N, the year of 8 ° of -12 ° of W marine sites i-th of each latitude section is calculated
Average SSTAi；
S3,6 marine climates and envirment factor are obtained, be respectively：
Climatic factor：NAOiIndex, envirment factor：30.5 ° N and 8 ° -12 ° of W marine sites annual SSTAi(SSTA1)、31.5°
N and 8 ° of -12 ° of W marine sites annual SSTAi(SSTA2), 32.5 ° N and 8 ° -12 ° of W marine sites annual SSTAi(SSTA3)、33.5°N
With 8 ° of -12 ° of W marine sites annual SSTAi(SSTA4), 34.5 ° N and 8 ° -12 ° of W marine sites annual SSTAi(SSTA5)；
The maximum output of octopus class fishery output is to obtain between S4, each annual octopus class fishery output divided by 1982-2015
Each annual octopus class Resources Richness Rate Index RA1 is obtained, siphonopods is caught between each annual siphonopods fishing total output divided by 1982-2015
The maximum output of total output is dragged for obtain each annual Resources of Cephalopods abundance combined index RA2；
S5,6 marine climates and envirment factor respectively with octopus class abundance index RA1 and Resources of Cephalopods abundance combined index
RA2 carries out correlation analysis, and selection obtains statistically significant (P<0.05) factor of influence, selection standard are phase relation
Several absolute values is more than or equal to 0.413；
S6, the factor of influence according to acquisition, respectively with octopus class abundance index RA1 and Resources of Cephalopods abundance combined index
RA2 establishes resource abundance forecast model using unitary linear model.
It is preferred that in step s 6, maximum envirment factor is influenceed on octopus class Resources Richness Rate Index RA1 for SSTA5, gas
The time factor is NAO, and octopus class Resources Richness Rate Index RA1 resource abundance forecast model is established based on envirment factor：RA1=a1+
B1*SSTA5, sample is carried out to octopus class resource abundance forecast model using RA1 values corresponding to each annual octopus class and SSTA5 values
Train to obtain a1 and b1 values；
Octopus class Resources Richness Rate Index RA1 resource abundance forecast model is established based on the natural environment and climate factor：RA1=a2
+ b2*SSTA5+b3*NAO, it is pre- to octopus class resource abundance using RA1 values, SSTA5 values and NAO values corresponding to each annual octopus class
Survey model and carry out sample training to obtain a2, b2 and b3 value；
The water temperature factor that maximum is influenceed on siphonopods resource abundance combined index RA2 is SSTA5, climatic factor NAO, is based on
Envirment factor establishes Resources of Cephalopods abundance combined index RA2 resource abundance forecast model：RA2=a3+b4*SSTA5, using each
RA2 values corresponding to annual siphonopods and SSTA5 values sample training is carried out to siphonopods resource abundance forecast model with obtain a3 and
B4 values；
Resources of Cephalopods abundance combined index RA2 resource abundance forecast model is established based on the natural environment and climate factor：RA2=
A4+b5*SSTA5+b6*NAO, using RA2 values, SSTA5 values and NAO values corresponding to each annual siphonopods to siphonopods resource abundance
Forecast model carries out sample training to obtain a4, b5 and b6 value.
It on the basis of common sense in the field is met, above-mentioned each optimum condition, can be combined, it is each preferably real to produce the present invention
Example.
The positive effect of the present invention is：
The present invention establishes statistically significant resource abundance forecast model, can scientific guidance in Morocco's marine site head
The production of sufficient class, also carry out efficiently fishing in Morocco marine site for Chinese relevant enterprise and science reference is provided.
Brief description of the drawings
Fig. 1 is 1980-2015 Morocco marine site cuttlefishes yield spatial distribution map.
Fig. 2 is 1980-2015 Morocco marine site octopus class yield spatial distribution map.
Fig. 3 is 1980-2015 Morocco marine site siphonopods yield spatial distribution map.
Fig. 4 is the flow chart of Morocco's marine site Resources of Cephalopods abundance Forecasting Methodology of present pre-ferred embodiments.
Embodiment
To make the purpose, technical scheme and advantage of the embodiment of the present invention clearer, below in conjunction with the embodiment of the present invention
In accompanying drawing, the technical scheme in the embodiment of the present invention is clearly and completely described, it is clear that described embodiment is
Part of the embodiment of the present invention, rather than whole embodiments.Based on the embodiment in the present invention, those of ordinary skill in the art
The every other embodiment obtained on the premise of creative work is not made, belongs to the scope of protection of the invention.
1st, material is collected
(1) production leadtime data.Downloaded in FAO's whole world fish production staqtistical data base and obtain 1982-
Moroccan fishing data in 2015, wherein, fishing data include cuttlefishes, octopus class and cephalopodous fishing production
Amount, unit is ton, sees Fig. 1-3.
(2) marine climate and envirment factor data.The National Weather Service of NOAA subordinate in the U.S.,
National Centers for Environmental Prediction, which are downloaded, obtains North Atlantic Ocean Arctic oscillation index NAO
Data, time series are 1982-2015.In Columbia University website http://iridl.ldeo.columbia.edu/
SOURCES/.IGOSS/.nmc/.Reyn_SmithOIv2/.mont hly/.ssta/ download ocean remote sensing and obtain table temperature anomaly
Average SSTA data, scope are 30 ° of -34 ° of N, 8 ° of W-12 ° of W marine sites.
2nd, data processing
(1) NAO data processings：Certain i years each moon NAO data are averaged, obtain certain annual NAOiIndex.
(2) SSTA data processings：On the basis of latitude, i.e., respectively 30.5 ° of N, 31.5 ° of N, 32.5 ° of N, 33.5 ° of N,
34.5 ° of N, calculate the average SSTA in the year of 8 ° of -12 ° of W marine sites i-th of a certain latitude sectioni。
By above-mentioned analysis, 6 weathers and the marine environment factor are obtained altogether, is respectively：NAOiIndex, 30.5 ° N and 8 °
W-12 ° of W marine sites annual SSTAi(SSTA1), 31.5 ° N and 8 ° W-12 ° of W marine sites annual SSTAi(SSTA2), 32.5 ° N and 8 °
W-12 ° of W marine sites annual SSTAi(SSTA3), 33.5 ° N and 8 ° W-12 ° of W marine sites annual SSTAi(SSTA4), 34.5 ° N and 8 °
W-12 ° of W marine sites annual SSTAi(SSTA5)。
(3) Resources of Cephalopods abundance index：Because Morocco's marine site siphonopods is mainly octopus class and cuttlefishes, with octopus
For main body, therefore Resources of Cephalopods abundance index includes octopus class abundance index (RA1) and Resources of Cephalopods abundance combined index
(RA2).Resources Richness Rate Index passes through standardization, i.e., each annual octopus class and cephalopodous yield difference divided by 1995-
Maximum output between 2015, i.e., respectively divided by 100606 and 150131.
3rd, analysis method
It is located in high latitude marine site in view of Morocco marine site, is just in the upper up-flow marine site of Canary Current formation, because
Abundant bottom nutritive salt is brought into upper strata by this upper up-flow hard, forms good fishing ground, and is the resources such as siphonopods
Abundant bait is provided.Therefore, patent of the present invention have selected the index of 5 table temperature average value, and 1 expression climate change
Index.Because the yield proportion of cuttlefishes is not so good as octopus class, therefore only consider that octopus class and Resources of Cephalopods abundance are pre-
Survey.
6 weathers and envirment factor respectively with octopus class abundance index (RA1) and Resources of Cephalopods abundance combined index (RA2)
Correlation analysis is carried out, selection obtains the factor of influence of statistically significant (P ＜ 0.05), and selection standard is coefficient correlation
Absolute value be greater than equal to 0.413 (in the case that sample is 21).
According to the factor of influence of above-mentioned acquisition, always refer to octopus class abundance index (RA1) and Resources of Cephalopods abundance respectively
Number (RA2) establishes resource abundance forecast model.
4th, analysis result
(1) the factor of influence selection of octopus class Resources Richness Rate Index (RA1)
Analysis shows, the coefficient correlation such as table 1 below with octopus class Resources Richness Rate Index (RA1).As shown in Table 1, counting
The significantly correlated factor is SSTA5 on, and the coefficient correlation of NAO and resource abundance is 0.3208.
The coefficient correlation statistical form of table 1
| The factor | SSTA1 | SSTA2 | SSTA3 | SSTA4 | SSTA5 | NAO |
| Coefficient correlation | -0.3306 | -0.3568 | -0.3766 | -0.4111 | -0.4260 | 0.3208 |
| Conspicuousness | P ＞ 0.05 | P ＞ 0.05 | P ＞ 0.05 | P ＞ 0.05 | P ＜ 0.05 | P ＞ 0.05 |
(2) the factor of influence selection of siphonopods class Resources Richness Rate Index (RA2)
Analysis shows, the coefficient correlation such as table 2 below with octopus class Resources Richness Rate Index (RA2).As shown in Table 2, counting
The significantly correlated factor is that the coefficient correlation of SSTA4 and SSTA5, NAO and resource abundance is 0.2942 on.
The coefficient correlation statistical form of table 2
| The factor | SSTA1 | SSTA2 | SSTA3 | SSTA4 | SSTA5 | NAO |
| Coefficient correlation | -0.2836 | -0.3221 | -0.3642 | -0.4156 | -0.4306 | 0.2942 |
| Conspicuousness | P ＞ 0.05 | P ＞ 0.05 | P ＞ 0.05 | P ＜ 0.05 | P ＜ 0.05 | P ＞ 0.05 |
(3) resource abundance forecast model is established
Using the envirment factor and climatic factor that above-mentioned influence is maximum, resource abundance is established respectively using unitary linear model
Forecast model.Its model is respectively：
1) octopus class Resources Richness Rate Index (RA1) forecast model based on envirment factor
RA1=a+b*SSTA5
Wherein, a=0.8178, b=-0.50349；A 95% confidential interval is [0.48417,1.15144]；The 95% of b
Confidential interval is [- 1.1016,0.00999], and coefficient correlation is 0.4260 (P=0.0496 ＜ 0.05).
2) Resources of Cephalopods abundance index (RA2) forecast model based on envirment factor
RA2=a+b*SSTA5
Wherein, a=0.79721, b=-0.45374；A 95% confidential interval is [0.50051,1.09392]；B's
95% confidential interval is [- 0.9104, -0.00291], and coefficient correlation is 0.4310 (P=0.0453 ＜ 0.05).
3) forecast model based on weather and envirment factor
Octopus class Resources Richness Rate Index (RA1) forecast model：
RA1=a+b1*SSTA5+b2*NAO
Wherein, a=0.8647, b1=-0.5351, b2=0.1942；A 95% confidential interval for [0.5434,
1.1861]；B1 95% confidential interval is [- 1.0238, -0.04635]；B2 95% confidential interval for [- 0.03209,
0.42058], coefficient correlation is 0.5538 (P=0.0370 ＜ 0.05).
Resources of Cephalopods abundance index (RA2) forecast model：
RA2=a+b1*SSTA5+b2*NAO
Wherein, a=0.8359, b1=-0.47983, b2=0.16029；A 95% confidential interval for [0.5466,
1.1253]；B1 95% confidential interval is [- 0.91991, -0.03975]；B2 95% confidential interval for [- 0.04351,
0.364088], coefficient correlation is 0.5410 (P=0.0443<0.05).
Summarize, as shown in figure 4, Morocco's marine site Resources of Cephalopods abundance Forecasting Methodology that the present embodiment provides, it includes
Following steps：
Step 101, the Moroccan fishing data of 1982-2015 are obtained, it is each to obtain the 1982-2015 North Atlantic Oceans
Month Arctic oscillation index NAO data, and obtain 30 ° of -34 ° of N, 8 ° of W-12 ° of W marine sites table temperature anomaly average SSTA data；
Wherein, the fishing data include cuttlefishes fishery output, octopus class fishery output and siphonopods fishing total yield
Amount；
Step 102, the NAO exponent datas of each each moon in year are averaged to the NAO that year is corresponded to acquisitioniIndex,
Respectively on the basis of 30.5 ° of N, 31.5 ° of N, 32.5 ° of N, 33.5 ° of N and 34.5 ° of N, 8 ° of -12 ° of W marine sites of each latitude section are calculated
The average SSTA in i yearsi；
Step 103,6 marine climates and envirment factor are obtained, be respectively：
Climatic factor：NAOiIndex, envirment factor：30.5 ° N and 8 ° -12 ° of W marine sites annual SSTAi(SSTA1)、31.5°
N and 8 ° of -12 ° of W marine sites annual SSTAi(SSTA2), 32.5 ° N and 8 ° -12 ° of W marine sites annual SSTAi(SSTA3)、33.5°N
With 8 ° of -12 ° of W marine sites annual SSTAi(SSTA4), 34.5 ° N and 8 ° -12 ° of W marine sites annual SSTAi(SSTA5)；
The maximum output of octopus class fishery output between step 104, each annual octopus class fishery output divided by 1982-2015
To obtain each annual octopus class Resources Richness Rate Index RA1, cephalopodium between each annual siphonopods fishing total output divided by 1982-2015
The maximum output of class fishing total output is to obtain each annual Resources of Cephalopods abundance combined index RA2；
Step 105,6 marine climates and envirment factor respectively with octopus class abundance index RA1 and Resources of Cephalopods abundance
Combined index RA2 carries out correlation analysis, and selection obtains statistically significant (P<0.05) factor of influence, selection standard are
The absolute value of coefficient correlation is more than or equal to 0.413；
Step 106, the factor of influence according to acquisition, it is total with octopus class abundance index RA1 and Resources of Cephalopods abundance respectively
Index RA2 establishes resource abundance forecast model using unitary linear model.
Although the foregoing describing the embodiment of the present invention, 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
On the premise of principle and essence from the present invention, various changes or modifications can be made to these embodiments, but these are changed
Protection scope of the present invention is each fallen within modification.
Claims (2)
1. a kind of Morocco marine site Resources of Cephalopods abundance Forecasting Methodology, it is characterised in that it comprises the following steps：
S1, the Moroccan fishing data of 1982-2015 are obtained, obtain each moon arctic great waves in the 1982-2015 North Atlantic Oceans
Dynamic index NAO data, and obtain 30 ° of -34 ° of N, 8 ° of W-12 ° of W marine sites table temperature anomaly average SSTA data；
Wherein, the fishing data include cuttlefishes fishery output, octopus class fishery output and siphonopods fishing total output；
S2, the NAO data of each each moon in year are averaged to the NAO that year is corresponded to acquisitioniIndex, respectively with 30.5 ° of N,
On the basis of 31.5 ° of N, 32.5 ° of N, 33.5 ° of N and 34.5 ° of N, 8 ° of -12 ° of W marine sites i-th year for calculating each latitude section is averaged
SSTAi；
S3,6 marine climates and envirment factor are obtained, be respectively：
Climatic factor：NAOiIndex, envirment factor：30.5 ° N and 8 ° -12 ° of W marine sites annual SSTAi(SSTA1), 31.5 ° of N and
8 ° of -12 ° of W marine sites annual SSTAi(SSTA2), 32.5 ° N and 8 ° -12 ° of W marine sites annual SSTAi(SSTA3), 33.5 ° of N and
8 ° of -12 ° of W marine sites annual SSTAi(SSTA4), 34.5 ° N and 8 ° -12 ° of W marine sites annual SSTAi(SSTA5)；
The maximum output of octopus class fishery output is each to obtain between S4, each annual octopus class fishery output divided by 1982-2015
Annual octopus class Resources Richness Rate Index RA1, siphonopods fishing is total between each annual siphonopods fishing total output divided by 1982-2015
The maximum output of yield is to obtain each annual Resources of Cephalopods abundance combined index RA2；
S5,6 marine climates and envirment factor respectively with octopus class abundance index RA1 and Resources of Cephalopods abundance combined index RA2
Correlation analysis is carried out, selection obtains statistically significant (P<0.05) factor of influence, selection standard are coefficient correlation
Absolute value be more than or equal to 0.413；
S6, the factor of influence according to acquisition, it is sharp with octopus class abundance index RA1 and Resources of Cephalopods abundance combined index RA2 respectively
Resource abundance forecast model is established with unitary linear model.
2. Resources of Cephalopods abundance Forecasting Methodology in Morocco marine site as claimed in claim 1, it is characterised in that in step S6
In, octopus class Resources Richness Rate Index RA1 is influenceed maximum envirment factor be SSTA5, climatic factor NAO, based on environment because
Son establishes octopus class Resources Richness Rate Index RA1 resource abundance forecast model：RA1=a1+b1*SSTA5, using each annual octopus
RA1 values corresponding to class and SSTA5 values carry out sample training to obtain a1 and b1 values to octopus class resource abundance forecast model；
Octopus class Resources Richness Rate Index RA1 resource abundance forecast model is established based on the natural environment and climate factor：RA1=a2+b2*
SSTA5+b3*NAO, mould is predicted to octopus class resource abundance using RA1 values, SSTA5 values and NAO values corresponding to each annual octopus class
Type carries out sample training to obtain a2, b2 and b3 value；
The water temperature factor that maximum is influenceed on siphonopods resource abundance combined index RA2 is SSTA5, climatic factor NAO, based on environment
The factor establishes Resources of Cephalopods abundance combined index RA2 resource abundance forecast model：RA2=a3+b4*SSTA5, using each year
RA2 values corresponding to siphonopods and SSTA5 values carry out sample training to obtain a3 and b4 values to siphonopods resource abundance forecast model；
Resources of Cephalopods abundance combined index RA2 resource abundance forecast model is established based on the natural environment and climate factor：RA2=a4+
B5*SSTA5+b6*NAO, it is pre- to siphonopods resource abundance using RA2 values, SSTA5 values and NAO values corresponding to each annual siphonopods
Survey model and carry out sample training to obtain a4, b5 and b6 value.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109360237A (en) * | 2018-12-07 | 2019-02-19 | 北京市水产科学研究所（国家淡水渔业工程技术研究中心） | A kind of prediction technique of total fish catches |
| CN109460860A (en) * | 2018-10-18 | 2019-03-12 | 上海海洋大学 | Argentinian squid Resources Prediction method based on Antarctic Oscillations index |
| CN109460867A (en) * | 2018-11-02 | 2019-03-12 | 上海海洋大学 | Chilean scad resource abundance medium- and long-term forecasting method based on ocean Nino index |
| CN109523071A (en) * | 2018-11-02 | 2019-03-26 | 上海海洋大学 | Saury resource abundance medium- and long-term forecasting method based on Pacific Ocean Oscillation Index |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103004664A (en) * | 2012-12-21 | 2013-04-03 | 上海海洋大学 | Method for forecasting northwest Pacific Ocean squids resource stock recruitment and application method thereof |
| CN103049659A (en) * | 2012-12-21 | 2013-04-17 | 上海海洋大学 | Method for forecasting stock recruitment of Peruvian open-sea Dosidicus gigas and method for applying same |
| CN106228456A (en) * | 2016-07-22 | 2016-12-14 | 上海海洋大学 | A kind of resource magnitude of recruitment Forecasting Methodology of Peru squid |
-
2017
- 2017-08-29 CN CN201710757009.0A patent/CN107403243A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103004664A (en) * | 2012-12-21 | 2013-04-03 | 上海海洋大学 | Method for forecasting northwest Pacific Ocean squids resource stock recruitment and application method thereof |
| CN103049659A (en) * | 2012-12-21 | 2013-04-17 | 上海海洋大学 | Method for forecasting stock recruitment of Peruvian open-sea Dosidicus gigas and method for applying same |
| CN106228456A (en) * | 2016-07-22 | 2016-12-14 | 上海海洋大学 | A kind of resource magnitude of recruitment Forecasting Methodology of Peru squid |
Non-Patent Citations (2)
| Title |
|---|
| E. G. DAWE等: "Ocean climate effects on the relative abundance of short-finned (Illex illecebrosus) and long-finned (Loligo pealeii) squid in the northwest Atlantic Ocean", 《FISHERIES OCEANOGRAPHY》 * |
| 汪金涛等: "基于产卵场环境因子的阿根廷滑柔鱼资源补充量预报模型研究", 《海洋学报》 * |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109460860A (en) * | 2018-10-18 | 2019-03-12 | 上海海洋大学 | Argentinian squid Resources Prediction method based on Antarctic Oscillations index |
| CN109460867A (en) * | 2018-11-02 | 2019-03-12 | 上海海洋大学 | Chilean scad resource abundance medium- and long-term forecasting method based on ocean Nino index |
| CN109523071A (en) * | 2018-11-02 | 2019-03-26 | 上海海洋大学 | Saury resource abundance medium- and long-term forecasting method based on Pacific Ocean Oscillation Index |
| CN109360237A (en) * | 2018-12-07 | 2019-02-19 | 北京市水产科学研究所（国家淡水渔业工程技术研究中心） | A kind of prediction technique of total fish catches |
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