Premium
Estimation of Fish Abundance Indices Based on Scientific Research Trawl Surveys
Author(s) -
Chen Jiahua,
Thompson Mary E.,
Wu Changbao
Publication year - 2004
Publication title -
biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.298
H-Index - 130
eISSN - 1541-0420
pISSN - 0006-341X
DOI - 10.1111/j.0006-341x.2004.00162.x
Subject(s) - statistics , estimator , abundance (ecology) , sampling (signal processing) , smoothing , population , econometrics , mathematics , fishery , computer science , biology , demography , filter (signal processing) , sociology , computer vision
Summary. The fish abundance index over an ocean region is defined here to be the integral of expected catch per unit effort (CPUE), approximated by the sum of expected CPUE over grid squares. When trawl surveys are done within grid squares selected according to a probability sampling design, several other sources of variation such as the fish population dynamics and the catching process are also involved. In such situations model‐assisted methods for estimating abundance, assessed under both design and model perspectives, have some advantages over purely design‐based methods such as the Horvitz–Thompson (HT) estimator or purely model‐based prediction approaches. This article develops model‐assisted empirical likelihood (EL) methods via loglinear regression and nonparametric smoothing. The methods are applied to grid surveys of the Grand Bank region carried out annually by Fishery Products International from 1996 through 2002. The HT and EL methods produce similar point estimates of abundance indices. Simulation results, however, indicate that the EL estimator under local linear smoothing is associated with smaller standard errors.