Optimized laying method for offshore marine fishery resource gill net survey

Abstract

The invention relates to an optimized laying method for offshore marine fishery resource gill net investigation, and belongs to the technical field of marine fishery resource investigation. The technical problems that in existing gill net investigation, the capture accumulation effect is obvious, variety coverage is incomplete, the fishing harvesting rate is low, and the data standardization degree is low are solved. According to the method, a laying mode (4h * 3) that the total time length is 12 h and each time period is divided into 4 h is adopted, the fishing harvesting rate can be remarkably increased, the coverage degree of the types of the fishery resources in the investigated water area is enhanced, community structure composition is truly reflected, a scientific and feasible technical scheme is provided for standardization of offshore marine fishery resource investigation, and the method is suitable for popularization and application. The method is suitable for survey work of fishery resources in Laizhou bay and sea areas such as near-shore shallow sea of similar temperate zones, marine ranching demonstration areas and the like.

Description

Technical Field

[0001] This invention relates to the field of marine fishery resource survey technology, specifically to an optimized deployment method for gillnet surveys of nearshore marine fishery resources. Background Technology

[0002] In recent years, the nearshore marine economy, including port-related industries, land reclamation, nuclear power projects, shipping, and marine ranching, has developed rapidly. Fisheries resource surveys and assessments have become a crucial foundation for environmental impact assessments of marine engineering projects and the construction of marine ranches. Gillnets, as a simple and controllable passive selective net, are currently the most commonly used tool for nearshore marine fisheries resource surveys. However, existing gillnet survey methods have many technical shortcomings, seriously affecting the accuracy and standardization of survey data.

[0003] On the one hand, gillnets exhibit species-selective capture efficiency, with a high probability of catching strong swimmers and irregularly shaped organisms, while their capture efficiency is low for weak swimmers and small individuals. While extending the deployment time can increase the capture rate for some species, it can lead to a cumulative catch effect. That is, as catch accumulates on the gillnet, the effective fishing space decreases, and the struggling signals of the captured organisms cause surrounding organisms to avoid them, resulting in a decrease in the catch rate per unit time. Related studies show that the gillnet deployment time and catch rate exhibit a typical non-linear dynamic relationship. The catch gradually increases over time in the initial deployment period, but gradually stabilizes in the later stages due to fish escapes, accumulated avoidance behaviors, and the net's capacity reaching its limit.

[0004] On the other hand, the efficiency of gillnet fishing is affected by a combination of factors, including the timing and duration of deployment, tidal conditions, and diurnal variation. Currently, there is no unified standard system for deployment duration and time periods both domestically and internationally. Domestically, gillnet deployment times vary greatly, with continuous operations of 12-16 hours in nearshore waters and short-term operations of 1-3 hours or even 8 days in nearshore and freshwater areas. Some studies specify specific time periods but lack consistent methods, leading to a lack of comparability in survey data and making it difficult to accurately reflect the true state of fishery resources.

[0005] Furthermore, fish's visual, auditory, and olfactory sensory systems detect the presence of gillnets and trigger avoidance behaviors, further exacerbating survey bias. Fish visual systems are extremely sensitive to changes in light intensity; the light gradient during the diurnal transition directly drives their vertical and horizontal migration behaviors. Fish are more active during this period, but existing deployment methods often fail to cover the fish community characteristics during this time, leading to incomplete species coverage and inaccurate community structure representation. Therefore, there is an urgent need for a gillnet deployment method that can balance capture efficiency and cumulative effects, cover key periods, and has a high degree of standardization, in order to improve the accuracy and reliability of nearshore marine fisheries resource surveys. Summary of the Invention

[0006] The purpose of this invention is to overcome the shortcomings of existing technologies and provide an optimized deployment method for gillnet surveys of nearshore marine fishery resources. By scientifically setting gillnet parameters, deployment patterns, and data statistics methods, this invention solves problems such as significant cumulative catch effects, incomplete species coverage, low catch rates, and low data standardization in existing technologies, thus providing technical support for the standardization of nearshore marine fishery resource surveys.

[0007] To achieve the above objectives, the present invention adopts the following technical solution: An optimized deployment method for gillnet surveys of nearshore marine fishery resources, comprising gillnet selection, survey area determination, deployment pattern setting, sampling area layout, and gillnet retrieval and data statistics; The gillnet selection is as follows: a double-layered gillnet is selected, with an outer mesh size of 35 cm and an inner mesh size of 5.6 cm. The gillnet's dimensions are 130 m in length and 10 m in height. This gillnet specification can accommodate the capture needs of fishery resources of different sizes, reduce selectivity bias caused by a single mesh size, and is suitable for capturing various fishery organisms in nearshore waters. The survey area was determined as follows: the survey area was selected in the nearshore sea area, and the area with homogeneous hydrological conditions was chosen. Such areas have weak spatial clustering effects, which can reduce the interference of environmental heterogeneity on the survey results and provide a stable environmental basis for standardized fishery resource surveys. The deployment pattern is set as follows: a segmented deployment pattern with a total duration of 12 hours is adopted, specifically divided into 3 time periods, each lasting 4 hours. Each time period involves deployment in a different sampling area to avoid interference from previous deployments. The specific deployment time periods are: the first time period is 17:30–21:30 (the day-night transition period when light changes from bright to dim), the second time period is 21:30–1:30 (the core nighttime period), and the third time period is 1:30–5:30 (the day-night transition period when light changes from dim to bright). This time period setting can cover the activity peaks of fish due to differences in visual adaptation, fully capture the temporal heterogeneity of the community, and adapt to the diurnal behavioral rhythms of fish. The sampling area layout is as follows: to avoid interference from previous meshes, the distance between sampling areas of two adjacent time periods is set to 2~3 nmile; Furthermore, four repeating stations were set up in each time period, with a station spacing of approximately 1 nmile. This multiple-repetition design reduced random errors, improved the reliability and representativeness of the survey data, and ensured that the results reflected the overall fishery resource status of the surveyed sea area.

[0008] The gillnet retrieval and data statistics are as follows: After each period of deployment, the gillnets are retrieved promptly, and the types, quality, and quantity of fish caught at each station are statistically analyzed to calculate the quality catch rate (unit: g·h). -1) and quantity catch rate (unit: ind·h -1 ), and perform data processing.

[0009] Furthermore, the data processing procedure is as follows: (1) Data standardization: After the original resource data is standardized by fourth root transformation, the species with resource volume of each station accounting for ≥3% of the total resource volume are screened and rare species are removed; (2) Normality test: Verify the normality of the data for the number of fishery resource species obtained at each station; (3) Statistical analysis: The similarity of community species was analyzed by Jaccard species composition similarity coefficient, the differences in community structure were compared by ANOSIM similarity analysis, the heterogeneity of catch rate at different time periods of the same pattern was analyzed by Friedman nonparametric test, and the differences in catch efficiency of different deployment patterns were compared by Wilcoxon rank sum test. (4) Perform significance analysis on the data. Furthermore, the normality of the data was verified using Shapiro-Wilk (n < 50) or Kolmogorov-Smirnov (n > 50).

[0010] The beneficial effects of this invention compared to the prior art are as follows: 1. Significantly Improved Catch Rate: This invention employs a 4-hour × 3-segment deployment pattern, which increases the quality catch rate and quantity catch rate by 97.80% and 210.26% respectively compared to the 12-hour continuous deployment pattern (12 hours × 1), and by 178.27% and 312.30% respectively compared to the 3-hour × 4-segment pattern. By rationally controlling the duration of each deployment, the cumulative effect of capture (avoidance behavior triggered by fish struggling signals and reduction of effective net space) is effectively mitigated, significantly improving the capture efficiency of fishery resources.

[0011] 2. More comprehensive species coverage: This method can capture 22 fishery resource species in the surveyed waters, which is 3 more species than the 12-hour continuous deployment mode and the 3-hour × 4 segmented mode. It also has more species in common with the latter two (16 and 15 species, respectively) and higher community composition similarity coefficients (0.70 and 0.60, respectively). It can more comprehensively cover the main fishery resource species in the surveyed waters and avoid species omissions due to improper time selection.

[0012] 3. More realistic community structure representation: The deployment period of this invention covers key nodes of day-night transition, enabling the capture of behavioral differences in fish caused by changes in visual adaptation. The temporal heterogeneity of community structure is prominent in each time period. F_r = 7.97, 7.25; P=0.02, 0.03), and the species composition similarity is reasonable (0.47~0.70), which can truly reflect the community structure composition and dynamic change characteristics of fishery resources in the surveyed waters, and provide reliable basic data for resource assessment.

[0013] 4. High degree of standardization: This method clarifies the specifications of gillnets, deployment duration, time period selection, sampling area layout, and data statistical methods, solving the problems of inconsistent deployment parameters and lack of data comparability in existing gillnet surveys. Its operational procedures are standardized and highly repeatable, providing a scientific and feasible technical solution for the standardization of nearshore marine fishery resource surveys. It can be widely applied to fishery resource surveys in Laizhou Bay and similar temperate nearshore shallow seas and marine ranching demonstration areas. Detailed Implementation

[0014] The present invention will be further described in detail below with reference to specific embodiments. These embodiments are only used to explain the present invention and are not intended to limit the scope of protection of the present invention.

[0015] Example 1

[0016] An optimized deployment method for gillnet surveys of nearshore marine fishery resources, comprising gillnet selection, survey area determination, deployment pattern setting, sampling area layout, and gillnet retrieval and data statistics; The gillnet selection is as follows: a double-layered gillnet is selected, with an outer mesh size of 35 cm and an inner mesh size of 5.6 cm. The gillnet's dimensions are 130 m in length and 10 m in height. This gillnet specification can accommodate the capture needs of fishery resources of different sizes, reduce selectivity bias caused by a single mesh size, and is suitable for capturing various fishery organisms in nearshore waters. The survey area was determined as follows: the survey area was selected in the nearshore sea area, and the area with homogeneous hydrological conditions was chosen. Such areas have weak spatial clustering effects, which can reduce the interference of environmental heterogeneity on the survey results and provide a stable environmental basis for standardized fishery resource surveys. The deployment mode is set as follows: a segmented deployment mode with a total duration of 12 hours is adopted, which is divided into 3 time periods, each with a deployment duration of 4 hours. Each time period is deployed in a different sampling area to avoid interference from the previous network to the subsequent survey.

[0017] As a specific implementation method, the deployment periods are set as follows: the first period is from 17:30 to 21:30 (the day-night transition period when the light changes from bright to dim), the second period is from 21:30 to 1:30 (the core nighttime period), and the third period is from 1:30 to 5:30 (the day-night transition period when the light changes from dim to bright). This time period setting can cover the activity peaks of fish due to differences in visual adaptation, fully capture the temporal heterogeneity of the community, and adapt to the diurnal behavioral rhythm of fish. The sampling area layout is as follows: to avoid interference from previous netting sessions, the sampling area distance between two adjacent time periods is set to 2-3 nmile; as a preferred implementation, four repeating stations are set in each time period, with a station spacing of about 1 nmile. The multiple repetition design reduces random errors, improves the reliability and representativeness of the survey data, and ensures that the results can reflect the overall fishery resource status of the surveyed sea area.

[0018] The gillnet retrieval and data statistics are as follows: After each period of deployment, the gillnets are retrieved promptly, and the types, quality, and quantity of fish caught at each station are statistically analyzed to calculate the quality catch rate (unit: g·h). -1 ) and quantity catch rate (unit: ind·h -1 ), and perform data processing.

[0019] As a preferred embodiment, the data processing procedure is as follows: (1) Data standardization: After the original resource data is standardized by fourth root transformation, the species with resource volume of each station accounting for ≥3% of the total resource volume are screened and rare species are removed; (2) Normality test: The normality of the data is verified for the number of fishery resource species captured at each station; as a specific implementation method, the Shapiro-Wilk (n < 50) or Kolmogorov-Smirnov (n > 50) method is used to verify the normality of the data. (3) Statistical analysis: The similarity of community species was analyzed by Jaccard species composition similarity coefficient, the differences in community structure were compared by ANOSIM similarity analysis, the heterogeneity of catch rate at different time periods of the same pattern was analyzed by Friedman nonparametric test, and the differences in catch efficiency of different deployment patterns were compared by Wilcoxon rank sum test. (4) Perform significance analysis on the data. As one specific implementation method, the data processing is completed based on Python statistical software, with α = 0.01 or 0.05.

[0020] Example 2

[0021] 1. Experiment time and location: From September 4 to 6, 2024, a gillnet survey of nearshore marine fishery resources was conducted in the northwestern waters of Laizhou Bay (37°24′~37°36′N, 119°06′~119°24′E). This area is affected by the Yellow River's freshwater runoff and has homogeneous hydrological conditions.

[0022] 2. Test materials: Double-layer barbed wire was selected, with an outer mesh diameter of 35 cm and an inner mesh diameter of 5.6 cm. The specifications were 130 m in length and 10 m in height.

[0023] 3. Experimental Method: The optimized deployment method described in this invention is employed, as follows: (1) Deployment mode: The total duration is 12 hours, and it is deployed in 3 time periods. The first time period is from 17:30 to 21:30, the second time period is from 21:30 to 1:30, and the third time period is from 1:30 to 5:30. The sampling area is spaced 2 to 3 nmile apart in each time period. (2) Station location setting: Four repeating stations are set for each time period, with a station spacing of 1 nmile; (3) Data statistics: After the gillnets were recovered, the types, quality and quantity of fish caught were counted. After the data was standardized, the Jaccard similarity coefficient, ANOSIM similarity analysis, Friedman nonparametric test and Wilcoxon rank-sum test were used for data analysis.

[0024] Experimental Results: This embodiment captured a total of 22 fishery resources, covering major dominant species such as spotted gudgeon, blue sardine, swimming crab, anchovy, and yellow croaker; the catch rate was 876.32 g·h. -1 The catch rate was 15.32 ind·h -1 This is significantly higher than the 12-hour continuous deployment method used in the same period (catch rate 443.04 g·h). -1 The catch rate was 4.94 ind·h -1 ) and 3h×4 segmented mode (quality catch rate 315.00 g·h) -1 The catch rate was 3.71 ind·h -1 The survey results showed that the similarity coefficient of community species in different time periods was 0.47 to 0.70, and the temporal heterogeneity of community structure was significant (P < 0.05), which can truly reflect the actual situation of fishery resources in this sea area.

[0025] The above experimental results verify the scientific validity and practicality of the method of the present invention. This method can effectively improve the accuracy and standardization of nearshore marine fishery resource surveys and provide reliable data support for fishery resource assessment and related engineering environmental impact assessments.

Claims

1. An optimized deployment method for gillnet surveys of nearshore marine fishery resources, characterized in that, The method includes selecting barbed wire, determining the survey area, setting the deployment pattern, laying out the sampling area, and recovering and statistically analyzing the barbed wire. The selected barbed wire is a double-layered structure, with an outer mesh size of 35 cm and an inner mesh size of 5.6 cm. The barbed wire has dimensions of 130 m in length and 10 m in height. The survey area was determined as follows: the survey area was selected in the nearshore sea area, specifically in a region with homogeneous hydrological conditions; The deployment mode is set as follows: a segmented deployment mode with a total duration of 12 hours is adopted, which is divided into 3 time periods, each with a deployment duration of 4 hours. Each time period is deployed in a different sampling area to avoid interference from the previous network to the subsequent survey. The sampling area layout is as follows: to avoid interference from previous meshes, the distance between sampling areas of two adjacent time periods is set to 2~3 nmile; The gillnet retrieval and data statistics are as follows: After the gillnets are deployed for each period, they are retrieved in a timely manner, and the types, quality and quantity of fish caught at each station are statistically analyzed. The quality catch rate and quantity catch rate are calculated, and the data is processed.

2. The optimized deployment method for gillnet survey of nearshore marine fishery resources according to claim 1, characterized in that, Four repeating stations are set up within each time period, with a station spacing of approximately 1 nmile.

3. The optimized deployment method for gillnet survey of nearshore marine fishery resources according to claim 1, characterized in that, The data processing procedure is as follows: (1) Data standardization: After the original resource data is standardized by fourth root transformation, the species with resource volume of each station accounting for ≥3% of the total resource volume are screened and rare species are removed; (2) Normality test: Verify the normality of the data for the number of fishery resource species obtained at each station; (3) Statistical analysis: The similarity of community species was analyzed by Jaccard species composition similarity coefficient, the differences in community structure were compared by ANOSIM similarity analysis, the heterogeneity of catch rate at different time periods of the same pattern was analyzed by Friedman nonparametric test, and the differences in catch efficiency of different deployment patterns were compared by Wilcoxon rank sum test. (4) Perform a significance analysis on the data.

4. The optimized deployment method for gillnet survey of nearshore marine fishery resources according to claim 1, characterized in that, The nearshore area mentioned refers to Laizhou Bay and similar temperate nearshore shallow seas.

5. The optimized deployment method for gillnet survey of nearshore marine fishery resources according to claim 3, characterized in that, The normality of the data was verified using the Shapiro-Wilk or Kolmogorov-Smirnov method.