| Fishery production surveys serve as the foundation for the assessment and management of fishery resources. A well-defined and reasonable sample size is essential for the accuracy and precision of the survey outcomes. This study compiled production surveys from major economic fishing ports in the northern South China Sea from 2008 to 2018, amassing 36,499 forms. It assumes these data accurately reflect the catch per unit effort (CPUE) of Decapterus maruadsi using various fishing gears. The study focuses on optimizing investigations by analyzing the CPUE of D. maruadsi from five distinct fishing operations: otter trawl, twin trawl, light purse seine, gillnet, and light falling-net. Our study has organized survey data by fishing type and stratified it by engine power and survey time. We have used proportional allocation for sample sizes and stratified random sampling without replacement for simulations. We have utilized computer simulations to conduct re-sampling of the CPUE of D. maruadsi obtained from five different types of fishing operations, employing relative estimation error (REE) and relative bias (RB) as evaluation metrics. We aimed to analyze the relationship between the CPUE of D. maruadsi and sample size in the northern South China Sea.
The port catch sampling survey provides production information for different types of fishing operations, with each survey form reflecting the CPUE data for a single voyage. Because CPUE for D.maruadsi varies among different types of fishing operations and across seasons within the same operation type, this study categorizes the survey forms by operation type and season. We calculate the CPUE for each operation type in different seasons and use these values as the "true values" for comparison. We consolidate survey data from various fishing gears across different power ranges, computing the CPUE for these forms. Furthermore, we employ CPUE as a metric to compare the fishing capacity and efficiency of different fishing gears targeting the species of interest. We have observed seasonal variations in the CPUE estimates for D.maruadsi across different fishing operations. By averaging the CPUE estimates over the four quarters, we found that the light purse seine method had the highest CPUE estimate at 3.577 kg.kW-1.d-1, while the gillnet method had the lowest at 0.143 kg.kW-1.d-1.
The results of this study indicate that there are differences in the distribution range of REE values for catch rate estimates among different types of fishing operations, but the overall trend of change is similar. Specifically, with an increase in sample size, the boxplot of REE values for CPUE estimates of each fishing gear shows a gradual decrease trend, while the RB values exhibit decreasing dispersion and tend to stabilize. It is worth noting that the distribution range of REE values for light purse seine and gill nets is relatively smaller compared to other fishing gears. We found that the minimum sample sizes required to estimate CPUE vary among different fishing operations, and the rules for determining these minimum sample sizes also differ. Otter trawl, pair trawl, and light purse seine determine the minimum sample size based on REE≤10%, while gillnets and light falling nets (except in winter) determine the minimum sample size based on REE≤5%. We also found that as the sample size reaches a certain point, the impact of increasing the number of survey forms on the estimation accuracy of average catch rates gradually decreases. Taking summer as an example, when the sample size reaches 600, the REE values of twin trawl, light purse seine, and light falling-net are below 10%; when the sample size reaches 800, the REE value of the otter trawl drops to within 10%; when the sample size increases to 1200, the REE value of the gillnet falls to within 10%, at which point the REE values of other operation types are all below 5%. If we continue to increase the sample size, the impact on sampling accuracy becomes increasingly minimal. In general, when the sample size reaches a certain value, the changes in REE and RB tend to stabilize, and the redundant portion of the sample size can be optimized. Even with a reduced sample size, the estimation accuracy can be ensured to a certain extent.
In this study, the minimum acceptable sample size for CPUE estimation varies across different fishing operations. Assuming the survey data from 2008 to 2018 accurately represents fishery production and considering an REE of less than 10%, the minimum number of survey trips required for CPUE estimation of D.maruadsi by operation type and season are: otter trawl (91, 68, 59, 86), twin trawl (41, 41, 82, 52), light purse seine (164, 87, 95, 57), gillnet (218, 218, 245, 191), and light falling-net with attractors (100, 81, 64, 43). On average, these correspond to 76 trips for the otter trawl, 54 for the twin trawl, 218 for the gillnet, 101 for the light purse seine, and 72 for the light falling-net with attractors. This study optimizes sample size using the mean CPUE of D.maruadsi as the survey target, and the evaluation results can provide reference for catch surveys in northern South China Sea fishing ports. |
