Volume 39 Issue 6
Jun.  2020
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Chunyang Sun, Yingbin Wang. Impacts of the sampling design on the abundance index estimation of Portunus trituberculatus using bottom trawl[J]. Acta Oceanologica Sinica, 2020, 39(6): 48-57. doi: 10.1007/s13131-020-1607-z
Citation: Chunyang Sun, Yingbin Wang. Impacts of the sampling design on the abundance index estimation of Portunus trituberculatus using bottom trawl[J]. Acta Oceanologica Sinica, 2020, 39(6): 48-57. doi: 10.1007/s13131-020-1607-z

Impacts of the sampling design on the abundance index estimation of Portunus trituberculatus using bottom trawl

doi: 10.1007/s13131-020-1607-z
Funds:  The National Key Research and Development Program of China under contract No. 2017YFA0604902; the Science and Technology Project of Zhoushan under contract No. 2017C41012.
More Information
  • Corresponding author: E-mail: ybwang@zjou.edu.cn
  • Received Date: 2019-06-02
  • Accepted Date: 2019-09-11
  • Available Online: 2020-12-28
  • Publish Date: 2020-06-25
  • In the survey of fishery resources, the sampling design will directly impact the accuracy of the estimation of the abundance. Therefore, it is necessary to optimize the sampling design to increase the quality of fishery surveys. The distribution and abundance of fisheries resource estimated based on the bottom trawl survey data in the Changjiang River (Yangtze River) Estuary-Hangzhou Bay and its adjacent waters in 2007 were used to simulate the “true” situation. Then the abundance index of Portunus trituberculatus were calculated and compared with its true index to evaluate the impacts of different sampling designs on the abundance estimation. Four sampling methods (including fixed-station sampling, simple random sampling, stratified fixed-station sampling, and stratified random sampling) were simulated. Three numbers of stations (9, 16 and 24) were assumed for the scenarios of fixed-station sampling and simple random sampling without stratification. While 16 stations were assumed for the scenarios with stratification. Three reaction distances (1.5 m, 3 m and 5 m) of P. trituberculatus to the bottom line of trawl were also assumed to adapt to the movement ability of the P. trituberculatus for different ages, seasons and substrate conditions. Generally speaking, compared with unstratified sampling design, the stratified sampling design resulted in more accurate abundance estimation of P. trituberculatus, and simple random sampling design is better than fixed-station sampling design. The accuracy of the simulated results was improved with the increase of the station number. The maximum relative estimation error (REE) was 163.43% and the minimum was 49.40% for the fixed-station sampling scenario with 9 stations, while 38.62% and 4.15% for 24 stations. With the increase of reaction distance, the relative absolute bias (RAB) and REE gradually decreased. Resource-intensive area and the seasons with high density variances have significant impacts on simulation results. Thus, it will be helpful if there are prior information or pre-survey results about density distribution. The current study can provide reference for the future sampling design of bottom trawl of P. trituberculatus and other species.
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