

FOLLOWUS
1.College of Fisheries, Ocean University of China, Qingdao 266003, China
2.Laboratory for Marine Fisheries Science and Food Production Processes, Qingdao Marine Science and Technology Center, Qingdao 266237, China
3.Field Observation and Research Station of Haizhou Bay Fishery Ecosystem, Ministry of Education, Qingdao 266003, China
bdxu@ouc.edu.cn
Received:18 June 2024,
Accepted:30 September 2024,
Online First:14 November 2024,
Published:01 September 2025
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MA Yihong,REN Yiping,ZHANG Chongliang,et al.Evaluation of adaptability of stratified survey scheme to ichthyoplankton sampling in an integrated fishery-independent survey[J].Journal of Oceanology and Limnology,2025,43(05):1668-1683.
MA Yihong,REN Yiping,ZHANG Chongliang,et al.Evaluation of adaptability of stratified survey scheme to ichthyoplankton sampling in an integrated fishery-independent survey[J].Journal of Oceanology and Limnology,2025,43(05):1668-1683. DOI: 10.1007/s00343-025-4162-9.
A comprehensive fishery-independent survey generally incorporates various specialized surveys and integrates different survey objectives to maximize benefits while accounting for cost limitations. It is important to evaluate the adaptability of the comprehensive survey for different taxon to get the optimal design. However
the validity and adaptability of ichthyoplankton sampling incorporated in a comprehensive fishery-independent survey program in estimating abundance of ichthyoplankton species is little known. This study included ichthyoplankton sampling in an integrated survey and assessed the appropriateness of survey design. The Kriging interpolation based on Gaussian models was used to estimate the values at unsurveyed locations based on the original ichthyoplankton survey data in the Haizhou Bay as the “true” values. The sampling performances of the ongoing stratified random sampling (StRS)
simple random sampling (SRS)
cluster sampling (CS)
hexagonal systematic sampling (SYS
h
)
and regular systematic sampling (SYS
r
) with different sample sizes in estimating ichthyoplankton abundance were compared in relative estimation error (REE)
relative bias (RB)
and coefficient of variation (CV) by computer simulation. The
ongoing StRS performed better than CS and SRS
but not as good as the two systematic sampling methods
and the current sample size in StRS design was insufficient to estimate ichthyoplankton abundance. The average REE values (meanREE) were significantly smaller in two systematic sampling designs than those in other three sampling designs
and the two systematic sampling designs could maintain good inter-annual stability of sampling performances. It is suggested that incorporating ichthyoplankton survey directly into stratified random fishery-independent surveys could not achieve the desired level of accuracy for survey objectives
but the accuracy can be improved by setting additional stations. The assessment framework presented in this study serves as a reference for evaluating the adaptability of integrated surveys to different objectives in other waters.
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