CN107688874A - Mauritanian marine site Resources of Cephalopods abundance Forecasting Methodology - Google Patents
Mauritanian marine site Resources of Cephalopods abundance Forecasting Methodology Download PDFInfo
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- 241000238366 Cephalopoda Species 0.000 title claims abstract description 31
- 238000000034 method Methods 0.000 title claims abstract description 10
- 241000238413 Octopus Species 0.000 claims abstract description 42
- 241000238371 Sepiidae Species 0.000 claims abstract description 41
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- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 2
- 241000287219 Serinus canaria Species 0.000 description 1
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- 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
- 230000001737 promoting effect Effects 0.000 description 1
- 150000003839 salts Chemical class 0.000 description 1
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Abstract
The present invention discloses a kind of Mauritanian marine site Resources of Cephalopods abundance Forecasting Methodology, obtains 1,982 2015 years Mauritanian fishing data, each moon Arctic oscillation index NAO in the North Atlantic Ocean, 16 ° of 22 ° of N, 16 ° of W, 20 ° of W marine sites table SSTA data；Obtain the NAO in corresponding yeariIndex, calculate the average SSTA in the year of 16 ° of 20 ° of W marine sites i-th of each latitude sectioni；Obtain 7 marine climates and envirment factor；Obtain each annual cuttlefishes Resources Richness Rate Index RA1, each annual octopus class Resources Richness Rate Index RA2, each annual Resources of Cephalopods abundance combined index RA3；7 marine climates carry out correlation analysis with RA1, RA2 and RA3 respectively with envirment factor, select P<0.05 factor of influence；According to the factor of influence of acquisition, resource abundance forecast model is established using unitary linear model with RA1, RA2 and RA3 respectively.
Description
Technical field
The present invention relates to Resources of Cephalopods abundance electric powder prediction, more particularly to a kind of Mauritanian marine site head
Sufficient class resource abundance Forecasting Methodology.
Background technology
Mauritanian marine site is located at the Atlantic Ocean central and east, and coastline is from cloth orchid family straits (20 ° of 36 ' N) to Saint Louis
(16 ° of 04 ' N), total length about 754km, 200-nautical-mile exclusive economic zone area reaches 23.4 ten thousand km2, (200m etc. is deep for continental shelf sea area
Within line) area is about 3.4 ten thousand km2, Northern Shelf width is larger, wherein most wide at Nouadhibou gulf and A Erjin shoals
Up to 80 nautical miles, and only have 30 nautical miles from the continental shelf width for carrying the angular south of meter Li Si, most important ocean current be Jia Nali cold currents from
North orientation south trend, brings cold water, Guinea's warm current is relatively weak in addition, but it is moved from south orientation Beiliu City, with Jia Nali cold currents
Mixed in cloth orchid family straits region, form significant upwelling, wherein containing substantial amounts of planktonic organism, be extremely suitable for fishery resources
Inhabit breeding, form one of world-renowned fishing ground.Siphonopods is that the fishery that most there is economic value in Mauritanian marine site provides
Source, its coastal waters are distributed.Siphonopods yield accounts for the 75% of economic fishery harvesting species, especially most with octopus quantity, and yield is maximum,
Economic value highest.
China begins participating in Mauritanian marine site siphonopods fishing operation from phase late 1980s, have accumulated big
The knowhow of amount, because inshore fishing ability is superfluous, cause the continuous decline of fishery resources, in addition the fishing of countries in the world bank
Industry management and access fishing condition are increasingly strict, therefore develop Mauritanian marine site Resources of Cephalopods for promoting the fishing of China ocean
The development tool of industry is of great significance.
Due to the species that siphonopods is 1 year, its resource abundance and marine environment are in close relations, climate change, ocean ring
The difference in border directly influences cephalopodous resource abundance, and then has influence on fish production and scientific management.Therefore, shadow is selected
The envirment factor of its resource abundance of sound is particularly important, and it is pre- to establish statistically significant resource abundance using envirment factor
Survey model, can scientific guidance in the cephalopodous production in Mauritanian marine site, be also Chinese relevant enterprise in Mauritania
Marine site carries out efficient fishing and provides guidance.
The content of the invention
The present invention is directed to problem and shortage existing for prior art, there is provided a kind of Mauritanian marine site Resources of Cephalopods
Abundance Forecasting Methodology.
The present invention is that solve above-mentioned technical problem by following technical proposals：
The present invention provides a kind of Mauritanian marine site Resources of Cephalopods abundance Forecasting Methodology, and its feature is that it includes
Following steps：
S1, the fishing data for obtaining 1982-2015 Mauritanias, it is each to obtain the 1982-2015 North Atlantic Oceans
Month Arctic oscillation index NAO data, and obtain 16 ° of -22 ° of N, 16 ° of W-20 ° 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 16.5 ° of N, 17.5 ° of N, 18.5 ° of N, 19.5 ° of N, 20.5 ° of N and 21.5 ° of N, 16 ° of -20 ° of W seas of each latitude section are calculated
The average SSTA in the year of domain i-thi；
S3,7 marine climates and envirment factor are obtained, be respectively：
Climatic factor：NAOiIndex, envirment factor：16.5 ° N and 16 ° -20 ° of W marine sites annual SSTAiBe designated as SSTA1,
17.5 ° N and 16 ° -20 ° of W marine sites annual SSTAiIt is designated as SSTA2,18.5 ° N and 16 ° -20 ° of W marine sites annual SSTAiIt is designated as
SSTA3,19.5 ° N and 16 ° -20 ° of W marine sites annual SSTAiIt is designated as SSTA4,20.5 ° N and 16 ° -20 ° of W marine sites annuals
SSTAiIt is designated as SSTA5,21.5 ° N and 16 ° -20 ° of W marine sites annual SSTAiIt is designated as SSTA6；
The maximum output of cuttlefishes fishery output is to obtain between S4, each annual cuttlefishes fishery output divided by 1982-2015
Each annual cuttlefishes Resources Richness Rate Index RA1 is obtained, octopus class is caught between each annual octopus class fishery output divided by 1982-2015
The maximum output of yield is dragged for obtain each annual octopus class Resources Richness Rate Index RA2, each annual siphonopods fishing total output divided by
The maximum output of siphonopods fishing total output is to obtain each annual Resources of Cephalopods abundance combined index RA3 between 1982-2015；
S5,7 marine climates and envirment factor respectively with cuttlefishes Resources Richness Rate Index RA1, octopus class abundance index
RA2 and Resources of Cephalopods abundance combined index RA3 carries out correlation analysis, and selection obtains statistically significant (P<0.05)
Factor of influence, selection standard for coefficient correlation absolute value be more than or equal to 0.329；
S6, the factor of influence according to acquisition, refer to respectively with corresponding cuttlefishes Resources Richness Rate Index RA1, octopus class abundance
Number RA2 and Resources of Cephalopods abundance combined index RA3 establishes resource abundance forecast model using unitary linear model.
It is preferred that in step s 6, cuttlefishes Resources Richness Rate Index RA1 is influenceed maximum envirment factor for SSTA5,
Climatic factor is NAO, and cuttlefishes Resources Richness Rate Index RA1 resource abundance forecast model is established based on envirment factor：RA1=
A1+b1*SSTA5, cuttlefishes resource abundance forecast model is carried out using RA1 values corresponding to each annual cuttlefishes and SSTA5 values
Sample training is to obtain a1 and b1 values；
Cuttlefishes Resources Richness Rate Index RA1 resource abundance forecast model is established based on climatic factor：RA1=a2+b2*
NAO, use RA1 values corresponding to each annual cuttlefishes and NAO values to cuttlefishes resource abundance forecast model carry out sample training with
Obtain a2 and b2 values；
The envirment factor that maximum is influenceed on octopus class Resources Richness Rate Index RA2 is SSTA4, climatic factor NAO, is based on
Envirment factor establishes octopus class Resources Richness Rate Index RA2 resource abundance forecast model：RA2=a3+b3*SSTA4, using each
RA2 values corresponding to annual octopus class and SSTA4 values sample training is carried out to octopus class resource abundance forecast model with obtain a3 and
B3 values；
Octopus class Resources Richness Rate Index RA2 resource abundance forecast model is established based on climatic factor：RA2=a4+b4*
NAO, use RA2 values corresponding to each annual octopus class and NAO values to octopus class resource abundance forecast model carry out sample training with
Obtain a4 and b4 values；
The envirment factor that maximum is influenceed on siphonopods resource abundance combined index RA3 is SSTA4, climatic factor NAO, base
Resources of Cephalopods abundance combined index RA3 resource abundance forecast model is established in envirment factor：RA3=a5+b5*SSTA4, adopt
RA3 values and SSTA4 values carry out sample training to obtain to siphonopods resource abundance forecast model corresponding to each annual siphonopods
A5 and b5 values；
Resources of Cephalopods abundance combined index RA3 resource abundance forecast model is established based on climatic factor：RA3=a6+
B6*NAO, sample instruction is carried out to siphonopods resource abundance forecast model using RA3 values corresponding to each annual siphonopods and NAO values
Practice to obtain a6 and b6 values.
It on the basis of common sense in the field is met, above-mentioned each optimum condition, can be combined, it is each preferably to produce the present invention
Example.
The positive effect of the present invention is：
The present invention establishes statistically significant resource abundance forecast model using marine climate and envirment factor,
Can scientific guidance in the cephalopodous production in Mauritanian marine site, also enter for Chinese relevant enterprise in Mauritanian marine site
The efficient fishing of row provides guidance.
Brief description of the drawings
Fig. 1 is 1980-2015 Mauritanias marine site cuttlefishes yield spatial distribution map.
Fig. 2 is 1980-2015 Mauritanias marine site octopus class yield spatial distribution map.
Fig. 3 is 1980-2015 Mauritanias marine site siphonopods yield spatial distribution map.
Fig. 4 is the flow chart of the Mauritanian 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, ordinary skill people
The every other embodiment that member is 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.Download and obtain in FAO's whole world fish production staqtistical data base
The fishing data of 1982-2015 Mauritanias, fishing data include cuttlefishes, octopus class and cephalopodous
Fishery output, unit are ton, see 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 NAO NAO indexes, when
Between sequence be 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 16 ° of -22 ° of N, 16 ° of W-20 ° 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 16.5 ° of N, 17.5 ° of N, 18.5 ° of N, 19.5 ° of N,
20.5 ° of N and 21.5 ° of N, calculate the average SSTA in the year of 16 ° of -20 ° of W marine sites i-th of a certain latitude sectioni。
By above-mentioned analysis, 7 marine climates and envirment factor are obtained altogether, they are NAO respectivelyiIndex, 16.5 ° of N
With 16 ° of -20 ° of W marine sites annual SSTAi(SSTA1), 17.5 ° N and 16 ° -20 ° of W marine sites annual SSTAi(SSTA2)、18.5°
N and 16 ° of -20 ° of W marine sites annual SSTAi(SSTA3), 19.5 ° N and 16 ° -20 ° of W marine sites annual SSTAi(SSTA4)、
20.5 ° N and 16 ° -20 ° of W marine sites annual SSTAi(SSTA5), 21.5 ° N and 16 ° -20 ° of W marine sites annual SSTAi
(SSTA6)。
(3) Resources of Cephalopods abundance index：Because Mauritanian marine site siphonopods is mainly cuttlefishes and octopus class,
Therefore Resources of Cephalopods abundance index includes cuttlefishes Resources Richness Rate Index (RA1), octopus class abundance index (RA2) and head
Sufficient class resource abundance combined index (RA3).Resources Richness Rate Index passes through standardization, i.e., each annual yield respectively divided by
Maximum output between 1982-2015, i.e., respectively divided by 7873,38607 and 44237.
3rd, analysis method
The upper up-flow marine site of Canary Current formation is in view of Mauritanian marine site.Ghana's profit ocean current belongs to east
Portion's boundary current, its ocean current, due to offshore wind action, forms upper up-flow during going down south, therefore its water temperature is relatively low, bottom
Abundant nutritive salt is brought into upper strata, forms good fishing ground, and the resource such as siphonopods provides abundant bait.Therefore, originally
Patent of invention have selected the index of 6 table temperature average value, and the index of 1 expression climate change.
7 marine climates and envirment factor respectively with cuttlefishes Resources Richness Rate Index (RA1), octopus class abundance index
(RA2) and Resources of Cephalopods abundance combined index (RA3) carries out correlation analysis, and selection obtains statistically significant (P<
0.05) factor of influence, selection standard are greater than equal to 0.329 for the absolute value of coefficient correlation.
According to the factor of influence of above-mentioned acquisition, respectively with cuttlefishes Resources Richness Rate Index (RA1), octopus class abundance index
(RA2) and Resources of Cephalopods abundance combined index (RA3) establishes resource abundance forecast model.
4th, analysis result
(1) the factor of influence selection of cuttlefishes Resources Richness Rate Index (RA1)
Analysis shows, the coefficient correlation such as table 1 below with cuttlefishes Resources Richness Rate Index (RA1).As shown in Table 1, counting
The significantly correlated factor has 5 factors such as NAO, SSTA3, SSTA4, SSTA5 and SSTA6 on, wherein, coefficient correlation is maximum
The factor be SSTA5.
The coefficient correlation statistical form of table 1
| The factor | NAO | SSTA1 | SSTA2 | SSTA3 | SSTA4 | SSTA5 | SSTA6 |
| Coefficient correlation | 0.344 | -0.289 | -0.309 | -0.348 | -0.370 | -0.371 | -0.355 |
| Conspicuousness | P ＜ 0.05 | 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 octopus 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 SSTA4 and NAO on, wherein using NAO coefficient correlation as maximum.
The coefficient correlation statistical form of table 2
| The factor | NAO | SSTA1 | SSTA2 | SSTA3 | SSTA4 | SSTA5 | SSTA6 |
| Coefficient correlation | 0.375 | -0.272 | -0.299 | -0.328 | -0.337 | -0.328 | -0.264 |
| Conspicuousness | P ＜ 0.05 | P ＞ 0.05 | P ＞ 0.05 | P ＞ 0.05 | P ＜ 0.05 | P ＞ 0.05 | P ＞ 0.05 |
(3) the factor of influence selection of Resources of Cephalopods abundance index (RA3)
Analysis shows, the coefficient correlation such as table 3 below with Resources of Cephalopods abundance index (RA3).As shown in Table 3, counting
The significantly correlated factor has 5 factors such as NAO, SSTA3, SSTA4, SSTA5 and SSTA6 on, wherein, coefficient correlation is maximum
The factor be SSTA4.
The coefficient correlation statistical form of table 3
| The factor | NAO | SSTA1 | SSTA2 | SSTA3 | SSTA4 | SSTA5 | SSTA6 |
| Coefficient correlation | 0.345 | -0.263 | -0.292 | -0.329 | -0.346 | -0.343 | -0.293 |
| Conspicuousness | P ＜ 0.05 | P ＞ 0.05 | P ＞ 0.05 | P ＜ 0.05 | P ＜ 0.05 | P ＜ 0.05 | P ＞ 0.05 |
(4) resource abundance forecast model is established
Using the marine environment factor and climatic factor that above-mentioned influence is maximum, money is established respectively using unitary linear model
Source abundance forecast model.Its model is respectively：
1) cuttlefishes Resources Richness Rate Index (RA1) forecast model
Forecast model based on envirment factor：
RA1=a+b*SSTA5
Wherein, a=0.57027, b=-0.14133；A 95% confidential interval is [0.19405,0.64649]；B's
95% confidential interval is [- 0.2686, -0.01406].Coefficient correlation is 0.3713 (P=0.0306<0.05).
Forecast model based on climatic factor：
RA1=a+b*NAO
Wherein, a=0.51886, b=0.161244；A 95% confidential interval is [0.45576,0.58197]；B's
95% confidential interval is [0.002821,0.31967].Coefficient correlation is 0.3441 (P=0.0463<0.05).
2) octopus class Resources Richness Rate Index (RA2) forecast model
Forecast model based on envirment factor：
RA2=a+b*SSTA4
Wherein, a=0.56359, b=-0.13398；A 95% confidential interval is [0.48009,0.647102]；B's
95% confidential interval is [- 0.26877, -0.00812].Coefficient correlation is 0.3370 (P=0.0496<0.05).
Forecast model based on climatic factor
RA2=a+b*NAO
Wherein, a=0.49558, b=0.19803；A 95% confidential interval is [0.42748,0.56367]；B's
95% confidential interval is [0.02785,0.36820].Coefficient correlation is 0.3758 (P=0.0238<0.05).
3) Resources of Cephalopods abundance index (RA3) forecast model
Forecast model based on envirment factor：
RA3=a+b*SSTA4
Wherein, a=0.610839, b=-0.1351；A 95% confidential interval is [0.52898,0.69269]；B's
95% confidential interval is [- 0.26723, -0.00297].Coefficient correlation is 0.3455 (P=0.0453<0.05).
Forecast model based on climatic factor
RA3=a+b*NAO
Wherein, a=0.558493, b=0.169413；A 95% confidential interval is [0.492406,0.62458]；B's
95% confidential interval is [0.003506,0.335321].Coefficient correlation is 0.3451 (P=0.0456<0.05).
Summarize, as shown in figure 4, the Mauritanian marine site Resources of Cephalopods abundance Forecasting Methodology that the present embodiment provides, its
Comprise the following steps：
Step 101, the fishing data for obtaining 1982-2015 Mauritanias, obtain 1982-2015 Beijing University
Each moon Arctic oscillation index NAO data in the West, and obtain 16 ° of -22 ° of N, 16 ° of W-20 ° of W marine sites table temperature anomaly average SSTA numbers
According to.
Wherein, the fishing data include cuttlefishes fishery output, octopus class fishery output and siphonopods fishing total yield
Amount.
Step 102, the NAO data of each each moon in year are averaged to the NAO that year is corresponded to acquisitioniIndex, respectively
On the basis of 16.5 ° of N, 17.5 ° of N, 18.5 ° of N, 19.5 ° of N, 20.5 ° of N and 21.5 ° of N, 16 ° of -20 ° of W of each latitude section are calculated
The average SSTA in the year of marine site i-thi。
Step 103,7 marine climates and envirment factor are obtained, be respectively：
Climatic factor：NAOiIndex, envirment factor：16.5 ° N and 16 ° -20 ° of W marine sites annual SSTAi (SSTA1)、
17.5 ° N and 16 ° -20 ° of W marine sites annual SSTAi(SSTA2), 18.5 ° N and 16 ° -20 ° of W marine sites annual SSTAi
(SSTA3), 19.5 ° N and 16 ° -20 ° of W marine sites annual SSTAi(SSTA4), 20.5 ° N and 16 ° -20 ° of W marine sites annuals
SSTAi(SSTA5), 21.5 ° N and 16 ° -20 ° of W marine sites annual SSTAi(SSTA6)。
The most high yield of cuttlefishes fishery output between step 104, each annual cuttlefishes fishery output divided by 1982-2015
Measure to obtain each annual cuttlefishes Resources Richness Rate Index RA1, chapter between each annual octopus class fishery output divided by 1982-2015
For the maximum output of fishes fishing yield to obtain each annual octopus class Resources Richness Rate Index RA2, each annual siphonopods catches total yield
The maximum output of siphonopods fishing total output is always referred to obtaining each annual Resources of Cephalopods abundance between amount divided by 1982-2015
Number RA3.
Step 105,7 marine climates and envirment factor respectively with cuttlefishes Resources Richness Rate Index RA1, octopus class abundance
Index RA2 and Resources of Cephalopods abundance combined index RA3 carries out correlation analysis, and selection obtains statistically significant (P<
0.05) factor of influence, selection standard are more than or equal to 0.329 for the absolute value of coefficient correlation.
Step 106, the factor of influence according to acquisition, respectively with corresponding cuttlefishes Resources Richness Rate Index RA1, octopus class
Abundance index RA2 and Resources of Cephalopods abundance combined index RA3 establish 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 Mauritanian marine site Resources of Cephalopods abundance Forecasting Methodology, it is characterised in that it comprises the following steps：
S1, the fishing data for obtaining 1982-2015 Mauritanias, obtain each moon north in the 1982-2015 North Atlantic Oceans
Pole Oscillation Index NAO data, and obtain 16 ° of -22 ° of N, 16 ° of W-20 ° 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 16.5 ° of N,
On the basis of 17.5 ° of N, 18.5 ° of N, 19.5 ° of N, 20.5 ° of N and 21.5 ° of N, the year of 16 ° of -20 ° of W marine sites i-th of each latitude section is calculated
Average SSTAi；
S3,7 marine climates and envirment factor are obtained, be respectively：
Climatic factor：NAOiIndex, envirment factor：16.5 ° N and 16 ° -20 ° of W marine sites annual SSTAi(SSTA1), 17.5 ° of N and
16 ° of -20 ° of W marine sites annual SSTAi(SSTA2), 18.5 ° N and 16 ° -20 ° of W marine sites annual SSTAi(SSTA3), 19.5 ° of N and
16 ° of -20 ° of W marine sites annual SSTAi(SSTA4), 20.5 ° N and 16 ° -20 ° of W marine sites annual SSTAi(SSTA5), 21.5 ° of N and
16 ° of -20 ° of W marine sites annual SSTAi(SSTA6)；
The maximum output of cuttlefishes fishery output is each to obtain between S4, each annual cuttlefishes fishery output divided by 1982-2015
Annual cuttlefishes Resources Richness Rate Index RA1, octopus class fishery output between each annual octopus class fishery output divided by 1982-2015
Maximum output to obtain each annual octopus class Resources Richness Rate Index RA2, each annual siphonopods fishing total output divided by 1982-
The maximum output of siphonopods fishing total output is to obtain each annual Resources of Cephalopods abundance combined index RA3 between 2015；
S5,7 marine climates and envirment factor respectively with cuttlefishes Resources Richness Rate Index RA1, octopus class abundance index RA2 and head
Sufficient class resource abundance combined index RA3 carries out correlation analysis, and selection obtains statistically significant (P<0.05) influence because
Son, selection standard are more than or equal to 0.329 for the absolute value of coefficient correlation；
S6, the factor of influence according to acquisition, respectively with corresponding cuttlefishes Resources Richness Rate Index RA1, octopus class abundance index RA2
With Resources of Cephalopods abundance combined index RA3 resource abundance forecast model is established using unitary linear model.
2. Mauritanian marine site Resources of Cephalopods abundance Forecasting Methodology as claimed in claim 1, it is characterised in that in step
In S6, the envirment factor maximum on cuttlefishes Resources Richness Rate Index RA1 influences is SSTA5, climatic factor NAO, based on environment
The factor establishes cuttlefishes Resources Richness Rate Index RA1 resource abundance forecast model：RA1=a1+b1*SSTA5, using each year crow
RA1 values corresponding to crafty class and SSTA5 values carry out sample training to obtain a1 and b1 values to cuttlefishes resource abundance forecast model；
Cuttlefishes Resources Richness Rate Index RA1 resource abundance forecast model is established based on climatic factor：RA1=a2+b2*NAO, adopt
RA1 values and NAO values carry out sample training to obtain a2 to cuttlefishes resource abundance forecast model corresponding to each annual cuttlefishes
With b2 values；
Octopus class Resources Richness Rate Index RA2 is influenceed maximum envirment factor be SSTA4, climatic factor NAO, based on environment because
Son establishes octopus class Resources Richness Rate Index RA2 resource abundance forecast model：RA2=a3+b3*SSTA4, using each annual octopus
RA2 values corresponding to class and SSTA4 values carry out sample training to obtain a3 and b3 values to octopus class resource abundance forecast model；
Octopus class Resources Richness Rate Index RA2 resource abundance forecast model is established based on climatic factor：RA2=a4+b4*NAO, adopt
RA2 values and NAO values carry out sample training to obtain a4 to octopus class resource abundance forecast model corresponding to each annual octopus class
With b4 values；
The envirment factor that maximum is influenceed on siphonopods resource abundance combined index RA3 is SSTA4, climatic factor NAO, based on environment
The factor establishes Resources of Cephalopods abundance combined index RA3 resource abundance forecast model：RA3=a5+b5*SSTA4, using each year
RA3 values corresponding to siphonopods and SSTA4 values carry out sample training to obtain a5 and b5 values to siphonopods resource abundance forecast model；
Resources of Cephalopods abundance combined index RA3 resource abundance forecast model is established based on climatic factor：RA3=a6+b6*NAO,
RA3 values corresponding to each annual siphonopods and NAO values is used to carry out sample training to siphonopods resource abundance forecast model to obtain
A6 and b6 values.
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| WO2020078439A1 (en) * | 2018-10-18 | 2020-04-23 | 上海海洋大学 | Method for predicting illex argentinus resource quantity on basis of antarctic oscillation index, and application thereof |
| JP2021520575A (en) * | 2018-10-18 | 2021-08-19 | 上海海洋大学Ｓｈａｎｇｈａｉ Ｏｃｅａｎ Ｕｎｉｖｅｒｓｉｔｙ | Prediction method of Argentine pine squid stock based on Antarctic Oscillation Index and its application |
| JP7044417B2 (en) | 2018-10-18 | 2022-03-30 | 上海海洋大学 | Prediction method of Argentine pine squid stock based on Antarctic Oscillation Index and its application |
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