WO2019042162A1 - 基于环境因子的西北非海域头足类渔场预报方法 - Google Patents
基于环境因子的西北非海域头足类渔场预报方法 Download PDFInfo
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- 241000238366 Cephalopoda Species 0.000 title claims abstract description 72
- 230000007613 environmental effect Effects 0.000 title claims abstract description 51
- 238000013277 forecasting method Methods 0.000 title abstract description 6
- 238000004519 manufacturing process Methods 0.000 claims abstract description 74
- 238000009826 distribution Methods 0.000 claims abstract description 43
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- G—PHYSICS
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- 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
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- A—HUMAN NECESSITIES
- A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
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- A01K61/00—Culture of aquatic animals
- A01K61/10—Culture of aquatic animals of fish
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- A23B—PRESERVING, e.g. BY CANNING, MEAT, FISH, EGGS, FRUIT, VEGETABLES, EDIBLE SEEDS; CHEMICAL RIPENING OF FRUIT OR VEGETABLES; THE PRESERVED, RIPENED, OR CANNED PRODUCTS
- A23B4/00—General methods for preserving meat, sausages, fish or fish products
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Definitions
- the invention relates to a cephalopod fishery forecasting method in the northwestern non-ocean sea area, in particular to a forecasting method for cephalopod fishery in northwest non-sea area based on environmental factors.
- Mauritania is a country in the western part of the African continent.
- the coastline is long and the marine environment is unique.
- the fishery is the main source of income for the national economy.
- the marine fishery resources have a storage capacity of more than 400 ⁇ l04t, especially the cephalopods are abundant, and it is also the main fishing object of China's ocean fishing vessels.
- the study of cephalopod resources and fisheries in the waters around Mauritania is of great significance for the efficient production of offshore trawlers in China.
- Feng Chunlei et al investigated the hydrological situation of the distribution of cephalopod fisheries in Mauritania, and analyzed the spatial structure and changes of various factors such as water mass, temperature, current, hydrological factors (water temperature, dissolved oxygen, salinity, chlorophyll), and discussed the research.
- the technical problem to be solved by the present invention is to provide an environmental factor-based forecasting method for the northwestern non-cephalopod fishery, and to study the effects of marine environmental factors and habitat indices on the northwestern non-cephalopod fishery, through the cephalopods of the northwestern non-fishing grounds.
- a method for forecasting cephalopod fishery in northwestern non-ocean based on environmental factors which comprises the following steps:
- Step 1 Obtain the catch production statistics of the cephalopod fishery in the northwestern non-ocean sea area for many years.
- the catch production statistics include working time, working water depth, operation network and total catch production;
- Step 2 Obtain marine environmental data corresponding to the catch production statistics, the marine environment data includes sea surface temperature SST, sea surface height distance average SSHA, and the marine environment data is monthly time resolution, 0.5° ⁇ 0.5° Spatial resolution
- Step 3 Study the relationship between the operation network and the output of the operation and the average network output in each interval as the index of the central fishery.
- Step 4 Establish the adaptability index SI of different environmental factors, and use the expert assignment method to calculate the habitat comprehensive index HSI under different weight schemes through different weight schemes, so as to obtain the distribution of the central fishery in the cephalopod fishery in the northwestern non-ocean.
- the sea area and the best weighting scheme in the distribution sea area is used to predict the center fishery.
- catch production statistics of the cephalopod fisheries in the northwestern non-sea area are based on data of 4-6 years.
- the marine environment data corresponding to the catch production statistics are obtained, and the marine environment data includes sea surface temperature SST, sea surface height average SSHA and chlorophyll concentration Chl-a, and SST is separated by 1 °C.
- For the spacing calculate the job nets, the job output ratio and the average net production in each interval, and then obtain the optimum range of the central fishery SST; calculate the spacing within each pitch by SSHA 10 cm apart.
- the operating network, the operating yield ratio and the average net output, and the optimal SSHA range of the central fishery is 0.01-1.0, 1.0-2.0, 2.0-5.0, 5.0-20.0 20.0 ⁇ 50.0mg/m 3 is the spacing, calculate the job network, the operation output ratio and the average net output in each interval, and then obtain the optimum range of the central fishery Chl-a; 10m is the distance, and the job network, the operation output ratio and the average net output in each interval are calculated, and the optimum depth of the center fishery is obtained.
- I SI_SST indicates the adaptability index based on sea surface temperature
- I SI_SSHA indicates the adaptability index based on the sea surface height distance
- I SI-CHL-a indicates the adaptability index based on chlorophyll concentration
- I SI_DEPTH indicates the water depth based adaptation Sex index
- X SST , X SSHA , X CHL-a , X DEPTH represent the values of sea surface temperature, sea surface height average, chlorophyll concentration, and water depth, respectively.
- the adaptability index SI is assigned 1; when there is no job network, the adaptability index SI is 0; when the job network is higher than the mean In the sea area, the fitness index SI is assigned a value of 0.5; when the operation network is lower than the mean sea level, the fitness index SI is assigned a value of 0.1.
- the HSI values and the set thresholds in the above five different weight schemes are analyzed separately, and the optimal weight scheme is compared to predict the central fishery of theixie cephalopod fishery.
- the SST minimum value of 15 °C, the SSHA minimum value of -45 cm, and the water depth minimum value of 15 m are used as the benchmarks, and the total nets of the catches are counted for each month at intervals of l °C, lOcm, and lOm.
- HSI X SST *I SI_SST +X SSHA *I SI_SSHA +X DEPTH *I SI_DEPTH ;
- I SI_SST represents the fitness index based on sea surface temperature
- I SI_SSHA represents the fitness index based on the sea level height
- I SI_DEPTH represents the water depth based adaptation index
- X SST , X SSHA , X DEPTH respectively represent the sea surface The value of the temperature, the sea level height, and the water depth.
- the fitness index SI of different environmental factors is established, and the value of the fitness index is given by the expert assignment method.
- the maximum operating network NETmax is set to the highest probability of catch distribution.
- the fitness index SI is assigned to l; when there is no job network, the fitness index is assigned a value of 0; when the operation network is higher than the mean, the fitness index is assigned a value of 0.5: when the job network is low In the mean sea area, the fitness index SI is assigned a value of 0.1.
- the HSI values and the set thresholds in the above five different weight schemes are separately analyzed, and the optimal weight scheme is compared to predict the center fishery.
- the present invention explores the influence of environmental factors with different weights on the cephalopod habitat model in West Africa, and obtains the main environmental factors and the best influence on the distribution of cephalopod habitats.
- the weighting scheme provides the basis for the prediction of the central fishery of the cephalopods in the northwestern non-ocean.
- FIG. 1 is a schematic flow chart of a fishery forecasting method of the present invention.
- FIG. 2 is a schematic flow chart of a method for forecasting a cephalopod fishery in theixie sea area according to the first embodiment of the present invention.
- Fig. 3 is a flow chart showing a method for predicting a cephalopod fishery in the Mauritania sea area according to the second embodiment of the present invention.
- cephalopods are a year of species, their fishery conditions and resource abundance are closely related to the marine environment.
- the differences in climate change and marine environment directly affect the habitat and resource abundance of cephalopods, which in turn affects fishery production and Scientific management. Therefore, it is extremely important to study the main environmental factors affecting the distribution of cephalopod habitats.
- the use of environmental factors to establish a fishery prediction model can scientifically guide the production of cephalopods in the northwestern non-ocean seas, and also provide efficient fishing production for related enterprises in the sea area. guide.
- Step 101 Obtain statistics on catch production of theixie fishery in 2012-2015.
- the catch production statistics include working time, longitude, latitude, working water depth, job network, and operation output.
- Step 102 Obtain marine environmental data corresponding to the catch production statistical data, where the marine environmental data includes a sea surface temperature SST, a sea surface height average SSHA, and a chlorophyll concentration Chl-a, and the marine environment data has a time resolution of 0.5° ⁇ 0.5° is the spatial resolution, and the statistical time is from January to May and from November to December in 2012-2015.
- step 103 the relationship between the work network and the output of the work and the average net output in each interval as the index of the central fishery is studied, and the relationship between the SST, the SSHA, the Chl-a and the water depth is studied.
- Step 104 Establish an adaptability index SI of different environmental factors, and use an expert assignment method to assign the value of the fitness index SI, and set the sea area with the highest job network as the sea area with the highest distribution probability of the central fishery, and the adaptive index SI is assigned. 1; When there is no job network, the adaptability index SI is 0; when the job network is higher than the mean, the adaptability index SI is 0.5; when the job network is lower than the mean, the adaptability index SI Assigned to 0.1.
- the job net can be regarded as an indicator of the fish, which is used to indicate the adaptability index of the habitat.
- Step 105 Calculate the habitat comprehensive index HSI under five different weighting schemes by using a formula:
- HSI Habitat suitability index
- I SI_SST , I SI_SSHA , I SI-CHL-a , and I SI_DEPTH are respectively adaptive indices based on surface temperature, sea surface height distance average, chlorophyll concentration, and water depth.
- X SST , X SSHA , X CHL-a , and X DEPTH are the values of the table temperature, the sea level height average, the chlorophyll concentration, and the water depth. A total of five different schemes with different weights are provided, and each scheme is as shown in Table 2 below.
- the HSI values and the set thresholds of the five different weight schemes are analyzed separately, and the optimal weight scheme is compared to predict the central fishery of theixie cephalopod fishery.
- the HSI values can be divided into 0-0.2, 0.2-0.4, 0.4-0.6, 0.6-0.8, and 0.8-1.0.
- the statistical analysis of the different values of HSI value >0.6 and HSI value ⁇ 0.4 in five different weight schemes is carried out to compare the best schemes for predicting the central fishery.
- the analysis results show that the distribution of cephalopod fishery is closely related to the surface temperature, and there are different suitable SST ranges in different months.
- the operation was mainly distributed in the SST range of 16 to 19 °C.
- the suitable SST range for high average net production was 16-17 °C and 18-19 °C, and the average yield was 130-153 kg.
- the operation was mainly distributed in the SST range of 15 to 19 °C.
- the suitable SST range for high average net production was 16-17 °C and 18-19 °C, and the average yield was 122-147 kg.
- the operation was mainly distributed in the SST range of 15 to 17 °C.
- the suitable SST range for high average net production was 15-16 °C, and the average yield was 89.16 kg.
- the operation was mainly distributed in the SST range of 18 to 23 °C.
- the suitable SST range for high average net output was 19-23 °C, and the average yield was 162-185 kg.
- the operation was mainly distributed in the SST range of 16 to 21 °C.
- the suitable SST range for high average net production was 20-21 °C, and the average yield was 457 kg.
- the analysis results show that the distribution of cephalopod fishery is closely related to the sea surface height anomaly, and there are different suitable SSHA ranges in different months.
- the work was mainly distributed in the SSHA range of -60 to -20 cm.
- the suitable SSHA range for high average net production was -60 to -30 cm, and the average yield was 124 to 143 kg.
- the operation was mainly distributed in the SSHA range of -60 to -30 cm.
- the suitable SSHA range for high average net production was -60 to -40 cm, and the average yield was 123 to 137 kg.
- the operation was mainly distributed in the SSHA range of -60 to -30 cm.
- the suitable SSHA range for high average net production was -60 to -40 cm, and the average yield was 96 to 101 kg.
- the operation was mainly distributed in the SSHA range of -50 to 10 cm.
- the suitable SSHA range for high average net production was -40 to -30 and -10 to 0 cm, and the average yield was 189 to 209 kg.
- the operation was mainly distributed in the SSHA range of -50 to 10 cm.
- the suitable SSHA range for high average net production was -50 to -40 cm, and the average yield was 558.69 kg.
- the analysis results show that the distribution of cephalopod fishery is closely related to chlorophyll concentration, and there are different suitable water depth ranges in different months.
- the operation was mainly distributed in the sea area of 0.01 to 50 mg/m 3 in the case of Chl-a, and the suitable Chl-a range of high average net production was 1.0 to 5.0 mg/m 3 , and the average yield was 96 to 127 kg.
- the operation was mainly distributed in the sea area of 0.01 to 20 mg/m 3 in the case of Chl-a.
- the suitable Chl-a range of high average net production was 1.0 to 20.0 mg/m 3 , and the average yield was 119 to 128 kg.
- the operation was mainly distributed in the sea area of 0.01 to 50 mg/m 3 in the case of Chl-a.
- the suitable Chl-a range of high average net production was 1.0 to 2.0 and 5.0 to 50 mg/m 3 , and the average yield was 99 to 110 kg.
- the operation was mainly distributed in the range of 0.01 to 20 mg/m 3 in the range of Chl-a, and the suitable Chl-a range of high average net yield was 0.01 to 5.0 mg/m 3 , and the average yield was 169 to 176 kg.
- the operation was mainly distributed in the sea area of 0.01 to 50 mg/m 3 in the case of Chl-a, and the suitable Chl-a range of high average net production was 2.0 to 5.0 mg/m 3 , and the average yield was 256.24 kg.
- the analysis results show that the distribution of cephalopod fishery is closely related to the working water depth, and there are different suitable water depth ranges in different months.
- the operation was mainly distributed in the water depth range of 20 to 90 m.
- the suitable water depth range of high average net production was 20-40 m, and the average yield was 131-140 kg.
- the operation was mainly distributed in the water depth range of 20 to 100 m.
- the suitable water depth range of high average net output was 20-50 m and 60-70 m, and the average yield was 117-141 kg.
- the operation was mainly distributed in the water depth range of 20 to 80 m.
- the suitable water depth range of high average net output was 70-80 m, and the average yield was 169 kg.
- the operation was mainly distributed in the water depth range of 30-80 m.
- the suitable water depth range of high average net output was 30-40 m, and the average yield was 246.49 kg.
- the operation was mainly distributed in the water depth range of 20 to 80 m.
- the suitable water depth range of high average net production was 20-50 m, and the average yield was 217-283 kg.
- the adaptability indices based on SST, SSHA, Chl-a and seabed water depth were established for each month (Table 3).
- the SST, SSHA, Chl-a, and water depth of the highest SI in January are 17-18 °C, -50-40 cm, 2.0-5.0 mg/m, and 30-40 m, respectively;
- SSHA, Chl-a and water depth are 16-17 °C, -50-40 cm, 2.03 ⁇ 5.0 mg/m, 30-40 m respectively;
- the highest SI SST, SSHA, Chl-a and water depth in March are 16-17 respectively.
- the habitat index (Table 3) of the weighted values set by different environmental factors related to the central fishery, and the occupational network and output of the period from January to March and from November to December in 2012-2015 are summarized by different HSI.
- Table 4 Average of the monthly operating nets, production ratios, and average net production in the five scenarios
- the habitat distribution of cephalopods in Morocco is closely related to environmental factors such as surface temperature, sea surface height anomaly and water depth.
- the monthly suitable environmental factors are different.
- the SST range in the operating fishery distribution area is 15-23 °C, SSHA The range is -60 to 10 cm, the chlorophyll concentration is 0 to 50 mg/m 3 , and the water depth ranges from 20 to 100 m, and the most suitable SST is 16 to 18 and 19 to 20 ° C, and the most suitable SSHA is -50 to -30 cm.
- the most suitable chlorophyll content is 1.0 to 5.0 mg/m 3 , and the most suitable water depth is 30 to 40 and 60 to 70 m.
- the weight of scheme 5 is optimal, and the weighting factors of SST, SSHA, CHL-a and water depth are 0.4, 0.4, 0.1 and 0.1, respectively, indicating that SST and SSHA have the greatest influence, water depth in the habitat index model.
- chlorophyll is again.
- the present embodiment provides a Mauritania cephalopod fishery prediction method based on habitat index, which includes the following steps:
- Step 101 Obtain statistics on catch production of the Mauritania fishery in 2010-2015.
- the catch production statistics include working time, working water depth, operation nets, and total catch production.
- the catch production statistics are from the Oceanic Fisheries Company. There are more than 10 trawlers with a time span of 2010-2015. Since May and June are often closed fishing seasons, the production statistics are from January to April and July to December.
- Step 102 Acquire marine environment data corresponding to the catch production statistical data, where the marine environment data includes a sea surface temperature SST and a sea surface height distance average SSHA, and the marine environment data has a time resolution of 0.5. ⁇ 0.5. For spatial resolution, the statistical time is from January to April and July to December of 2010-2015.
- Step 103 separately calculate the operation network times, the working water depth, and the total catch yield of different time periods in each month of 2010-2015, and filter and collate the statistical data, and use the average net output as the central fishery index, and utilize
- the expert assignment method establishes the adaptability index, and then designs different weight schemes to calculate and compare the spatial distribution of the Mauritian cephalopod fishery and its relationship with the marine environment and the best weight scheme in the sea area corresponding to the Mauritanian cephalopod fishery. This relationship is the optimal SST, SSHA and operating depth range for the central fishery.
- the sea level height average interval and the most suitable water depth interval are examples of the sea surface temperature range.
- the Suitability index SI of different environmental factors is established, and the value of the fitness index is given by the expert assignment method.
- the maximum job network NETmax is set as the catch distribution. In the sea area with the highest probability, the fitness index is assigned a value of 1; when there is no job network, the fitness index is assigned a value of 0; when the operation network is higher than the mean, the fitness index is assigned a value of 0.5; In the sea below the mean, the fitness index SI is assigned a value of 0.1. See Table 5:
- HSI Hazard suitability index
- Xsst represents the weight of the sea surface temperature
- X SSHA represents the weight of the sea surface height from the average value
- X DEPTH represents the weight of the water depth.
- HSI X SST *I SI_SST +X SSHA *I SI_SSHA +X DEPTH *I SI_DEPTH to calculate the habitat comprehensive index HSI under five different weight schemes, where: I SST represents the adaptability index based on sea surface temperature; I SSHA represents the fitness index based on the sea level height mean; I SI_DEPTH represents the water depth based adaptability index.
- the HSI values can be divided into 0-0.2, 0.2-0.4, 0.4-0.6, 0.6-0.8, and 0.8-1.0.
- the statistical analysis of the different values of HSI value >0.6 and HSI value ⁇ 0.4 in five different weight schemes is carried out to compare the best schemes for predicting the central fishery.
- the analysis results show that the distribution of non-cephalopod fish farms in Northwest China is closely related to sea surface temperature, and there are different suitable SST ranges in different months.
- the main SST of the operating fishery are 16-20 °C, 16-19 °C, 16-19 °C, 17-18 °C; the suitable SST of high average net output is 15-21 °C, 15-19 respectively.
- °C and 20 to 21 ° C, 15 to 20 ° C, 17 to 20 ° C, the corresponding high average net production is 34 ⁇ 51kg, 30 ⁇ 43kg, 26 ⁇ 37kg, 26 ⁇ 30kg.
- the main SST of the operating fishery are 20-21 °C, 21-22 °C and 23-26 °C, 25-27 °C, 21-22 °C, 19-21 °C, 20-21 °C and 23 ⁇ 24 ° C;
- suitable SST of high average net output is 20 ⁇ 22 ° C, 21 ⁇ 24 ° C, 24-27 ° C, 20 ⁇ 22 ° C, 18 - 21 ° C, 20: - 22 ° C and 23: - 24 ° C
- the output of high average net times is 77-92kg, 54-63kg, 29-34kg, 99-103kg, 36-52kg, 31--47kg.
- the analysis results show that the distribution of cephalopod fishery is closely related to the sea surface height anomaly, and there are different suitable SSHA ranges in different months.
- the main SSHA of the operating fishery are -35 ⁇ -25cm and -5 ⁇ 5cm, -45 ⁇ -35cm and -5 ⁇ 5cm, -5 ⁇ 5cm, -5 ⁇ 5cm; high average net output Suitable SSHA are -40 ⁇ -20cm, -50 ⁇ -30cm, -45 ⁇ -35cm, -5 ⁇ 15cm, the corresponding high average net production is 37 ⁇ 47kg, 47 ⁇ 48kg, 59.22kg, 28 ⁇ 35kg.
- the main SSHA of the operating fishery are -35 to 25 cm, -25 to -15 cm, -35 to -25 cm, and -5 to 5 cm, -35 to -25 cm, -25 to -15 cm, and -5 to 5 cm.
- the suitable SSHA for high average net production is -45 ⁇ -15cm, -45 ⁇ -15cm, -35 ⁇ -15cm and -5 ⁇ 5cm, -35 ⁇ -15cm, -35 ⁇ -15cm and -5 ⁇ 5cm , -5 ⁇ 5cm, the corresponding high average net production is 67 ⁇ 80kg, 48 ⁇ 56kg, 27 ⁇ 40kg, 81 ⁇ 104kg, 42 ⁇ 50kg, 36.96kg.
- the analysis results show that the distribution of cephalopod fishery is closely related to the working water depth, and there are different suitable water depth ranges in different months.
- the main water depths of the operating fishery are 45-65m, 55-75m, 55-85m, 65-75m and 85-95m respectively;
- the suitable water depths for high-average mesh production are 55-65m, 45-75m, respectively.
- the corresponding high average net production is 44.32 kg, 30 to 43 kg, 28 to 38 kg, and 31.96 kg, respectively.
- the main water depths of the operating fishery are 15 to 25 m, 15 to 25 m and 45 to 55 m, 55 to 75 m, 55 to 65 m, 55 to 65 m, 25 to 35 m and 45 to 055 m, respectively.
- Suitable water depths are 15 to 25 m and 55 to 75 m, 15 to 25 m, 45 to 75 m, 55 to 65 m, 55 to 65 m, 25 to 35 m, and 45 to 55 m, respectively, and the corresponding high average net yields are 58 to 77 kg, respectively. 57.43kg, 27 ⁇ 39kg, 99.62kg, 45.12kg, 36 ⁇ 38kg.
- the maximum SST, SSHA, and water depth of SI in January are 16 to 17 ° C, -5 to 5 cm, and 55 to 65 m, respectively.
- the maximum SST, SSHA, and water depth of SI in February are 16 to 17 ° C, respectively.
- ⁇ 5cm, 65 ⁇ 75m The maximum SST, SSHA and water depth of SI in March are 18 ⁇ 19°C, -5 ⁇ Ocm, 75 ⁇ 85m respectively;
- the largest SST, SSHA and water depth of SI in July are 20 ⁇ 21°C, respectively. -30 ⁇ -25cm, 20 ⁇ 25m; September's largest SST, SSHA and water depth are 26 ⁇ 27 ° C, -5 ⁇ 5cm, 55 ⁇ 65m.
- Table 7 Adaptability index based on sea surface temperature, sea surface height anomaly and water depth from January to March, July and September
- the HSI When the HSI is above 0.6, it is generally the central fishery. At this time, the greater the proportion of the job network and the proportion of the output, the better the corresponding weight scheme model. It can be seen from Table 8 that the scheme l is the best, the HSI value is >0.6, the proportion of the operation network and the proportion of the output are 64.2826 and 67.6196, respectively, and the average net output is 44 to 51 kg; the worst of the scheme 5, the HSI value is >0.6, the operation network The secondary specific gravity and the proportion of production are 57.8826 and 61.92%, respectively, and the average net output is 45 to 48 kg.
- Table 8 analyzes the number of job nets, the proportion of job output, and the average net production in January-April, July, and September 2010 based on the habitat index model of the five scenarios.
- scheme l is optimal (weights for SST, SSHA, and water depth are 0.6, 0.3, and 0.1, respectively), and scheme 5 (weights for SST, SSHA, and water depth are both l/3)
- SST has the greatest impact, followed by SSHA, and the water depth is the last.
- the present invention explores the influence of environmental factors with different weights on the cephalopod habitat model in West Africa, and obtains the main environmental factors and the best influence on the distribution of cephalopod habitats.
- the weighting scheme provides the basis for the prediction of the central fishery in the cephalopods of West Africa.
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Abstract
Description
Claims (10)
- 一种基于环境因子的西北非海域头足类渔场预报方法,其特征在于包括以下步骤:步骤一:获取多年西北非海域头足类渔场的渔获生产统计数据,该渔获生产统计数据包括作业时间、作业水深、作业网次以及渔获物总产量;步骤二:获取该渔获生产统计数据对应的海洋环境数据,该海洋环境数据包括海表温度SST、海面高度距平均值SSHA,该海洋环境数据以月为时间分辨率、0.5°×0.5°为空间分辨率;步骤三:以作业网次、作业产量所占比率以及每个区间内的平均网次产量作为中心渔场的指标,研究其与步骤二所述海洋环境数据之间的关系;步骤四:建立不同环境因子的适应性指数SI,并采用专家赋值法通过不同的权重方案计算得到不同权重方案下的栖息地综合指数HSI,从而获得西北非海域头足类渔场的中心渔场的分布海域,并得出该分布海域内最佳的权重方案,用于预测中心渔场。
- 如权利要求1所述的基于环境因子的西北非头足类渔场预报方法,其特征在于:所述西北非海域头足类渔场的渔获生产统计数据采用4-6年的数据。
- 如权利要求1或2所述的基于环境因子的西北非海域头足类渔场预报方法,其特征在于:对于西北非的摩洛哥渔场,获取该渔获生产统计数据对应的海洋环境数据,该海洋环境数据包括海表温度SST、海面高度距平均值SSHA和叶绿素浓度Chl-a,以SST相隔1℃为间距,计算出每个间距内的作业网次、作业产量比率以及平均网次产量,并依此得出最适宜的中心渔场SST的范围;以SSHA相隔10cm为间距,计算出每个间距内的作业网次、作业产量比率以及平均网次产量,并依此得出最适宜的中心渔场SSHA的范围;以Chl-a的含量在0.01~1.0、1.0~2.0、2.0~5.0、5.0~20.0、20.0~ 50.0mg/m 3为间距,计算出每个间距内的作业网次、作业产量比率以及平均网次产量,并依此得出最适宜的中心渔场Chl-a的范围;以水深相隔10m为间距,计算出每个间距内的作业网次、作业产量比率以及平均网次产量,并依此得出最适宜的中心渔场水深的范围。
- 如权利要求3所述的基于环境因子的西北非海域头足类渔场预报方法,其特征在于:对于包括海表温度SST、海面高度距平均值SSHA和叶绿素浓度Chl-a的海洋环境数据建立不同环境因子的适应性指数SI,采用如下公式计算不同权重方案下的栖息地综合指数HSI:HSI=X SST*I SI_SST+X SSHA*I SI_SSHA+X CHL-a*I SI-CHL-a+X DEPTH*I SI_DEPTH;其中:I SI_SST表示基于海表温度的适应性指数;I SI_SSHA表示基于海面高度距平均值的适应性指数;I SI-CHL-a表示基于叶绿素浓度的适应性指数;I SI_DEPTH表示基于水深的适应性指数;X SST、X SSHA、X CHL-a、X DEPTH分别表示海表温度、海面高度距平均值、叶绿素浓度、水深所占权重的值。
- 如权利要求4所述的基于环境因子的西北非海域头足类渔场预报方法,其特征在于:设定作业网次最高的海域为中心渔场的分布概率最高的海域,则适应性指数SI赋值为1;当没有作业网次则适应性指数SI赋值为0;当作业网次高于均值的海域,则适应性指数SI赋值为0.5;当作业网次低于均值的海域,则适应性指数SI赋值为0.1。
- 如权利要求4所述的基于环境因子的西北非海域头足类渔场预报方法,其特征在于:对于海表温度、海面高度距平均值、叶绿素浓度、水深所占权重的值采用以下五种权重方案:方案1:X SST为0.25,X SSHA为0.25,X CHL-a为0.25,X DEPTH为0.25;方案2:X SST为0,X SSHA为0.9,X CHL-a为0,X DEPTH为0.1;方案3:X SST为0.1,X SSHA为0.1,X CHL-a为0,X DEPTH为0.8;方案4:X SST为0.9,X SSHA为0.1,X CHL-a为0,X DEPTH为0;方案5:X SST为0.4,X SSHA为0.4,X CHL-a为0.1,X DEPTH为0.1;分别分析上述五种不同权重方案中HSI值与设定阈值的大小,从而比较得出最佳权重方案,用于预测摩洛哥头足类渔场的中心渔场。
- 如权利要求1或2所述的基于环境因子的西北非海域头足类渔场预报方法,其特征在于:对于西北非的毛里塔尼亚渔场,分别以SST最小值15℃、SSHA最小值-45cm、水深最低值15m做基准,对应间隔l℃、lOcm、lOm,统计各月的渔获物总网次,总产量和天数,求出每SST l℃、SSHA lOcm、水深lOm间隔内渔获物网次所占的比例、产量所占的比例、平均网次产量,由此得到各月份中心渔场最适宜的海表温度区间、最适宜的距海面高度平均值区间以及最适宜的水深区间。
- 如权利要求7所述的基于环境因子的西北非海域头足类渔场预报方法,其特征在于:对于对应的海洋环境数据,采用如下公式计算不同权重方案下的栖息地综合指数HSI:HSI=X SST*I SI_SST+X SSHA*I SI_SSHA+X DEPTH*I SI_DEPTH;其中:I SI_SST表示基于海表温度的适应性指数;I SI_SSHA表示基于海面高度距平均值的适应性指数;I SI_DEPTH表示基于水深的适应性指数;X SST、X SSHA、X DEPTH分别表示海表温度、海面高度距平均值、水深所占权重的值。
- 如权利要求8所述的基于环境因子的西北非海域头足类渔场预报方法,其特征在于:以作业网次的频度分布图为基础,建立不同环境因子的适应性指数SI,采用专家赋值法赋予适应性指数SI的值,设定最高作业网次NETmax为渔获物分布概率最高的海域,则适应性指数SI赋值为l;当没有 作业网次则适应性指数SI赋值为0;当作业网次高于均值的海域,则适应性指数SI赋值为0.5:当作业网次低于均值的海域,则适应性指数SI赋值为0.1。
- 如权利要求8所述的基于环境因子的西北非海域头足类渔场预报方法,其特征在于:对于海表温度、海面高度距平均值、水深所占权重的值采用以下五种权重方案:方案l:X SST为0.6,X SSHA为0.3,X DEPTH为0.1;方案2:X SST为0.5,X SSHA为0.2,X DEPTH为0.3;方案3:X SST为0.4,X SSHA为0.2,X DEPTH为0.4;方案4:X SST为0.3,X SSHA为0.4,X DEPTH为0.3;方案5:X SST为1/3,X SSHA为1/3,X DEPTH为1/3;分别分析上述五种不同权重方案中HSI值与设定阈值的大小,从而比较得出最佳权重方案,用于预测中心渔场。
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