The systematic sampling for inferring the survey indices of Korean groundfish stocks

Fisheries and Aquatic Sciences

Young IL Seo¹  Saang-Yoon Hyun² 

[1] Coastal Water Fisheries Resources Research Division, National Institute of Fisheries Science;College of Fisheries Sciences, Pukyong National University;

关键词: Groundfish;    Precision;    Systematic sampling;    Survey index;    Uncertainty;   

DOI  :  10.1186/s41240-018-0102-3

来源: DOAJ

【 摘 要 】

Abstract The Korean bottom trawl survey has been deployed on a regular basis for about the last decade as part of groundfish stock assessments. The regularity indicates that they sample groundfish once per grid cell whose sides are half of one latitude and that of one longitude, respectively, and whose inside is furthermore divided into nine nested grids. Unless they have a special reason (e.g., running into a rocky bottom), their sample location is at the center grid of the nine nested grids. Given data collected by the survey, we intended to show how to appropriately estimate not only the survey index of a fish stock but also its uncertainty. For the regularity reason, we applied the systematic sampling theory for the above purposes and compared its results with a reference, which was based on the simple random sampling. When using the survey data about 11 fish stocks, collected by the spring and fall surveys in 2014, the survey indices of those stocks estimated under the systematic sampling were overall more precise than those under the simple random sampling. In estimates of the survey indices in number, the standard errors of those estimates under the systematic sampling were reduced from those under the simple random sampling by 0.23~27.44%, while in estimates of the survey indices in weight, they decreased by 0.04~31.97%. In bias of the estimates, the systematic sampling was the same as the simple random sampling. Our paper is first in formally showing how to apply the systematic sampling theory to the actual data collected by the Korean bottom trawl surveys.

【 授权许可】

Unknown