Estimating anglerfish abundance from trawl surveys, and related problems
Abstract
The content of this thesis was motivated by the need to estimate anglerfish abundance
from stratified random trawl surveys of the anglerfish stock which occupies
the northern European shelf (Fernandes et al., 2007). The survey was conducted
annually from 2005 to 2010 in order to obtain age-structured estimates of absolute
abundance for this stock. An estimation method is considered to incorporate statistical models for herding, length-based net retention probability and missing age data and uncertainty from all of these sources in variance estimation.
A key component of abundance estimation is the estimation of capture probability.
Capture probability is estimated from the experimental survey data using various
logistic regression models with haul as a random effect. Conditional on the estimated
capture probability, a number of abundance estimators are developed and applied to
the anglerfish data. The abundance estimators differ in the way that the haul effect is incorporated. The performance of these estimators is investigated by simulation. An estimator with form similar to that conventionally used to estimate abundance from distance sampling surveys is found to perform best.
The estimators developed for the anglerfish survey data which incorporate random
effects in capture probability have wider application than trawl surveys. We examine
the analytic properties of these estimators when the capture/detection probability is
known. We apply these estimators to three different types of survey data in addition
to the anglerfish data, with different forms of random effects and investigate their
performance by simulation. We find that a generalization of the form of estimator
typically used on line transect surveys performs best overall. It has low bias, and
also the lowest bias and mean squared error among all the estimators we considered.
Type
Thesis, PhD Doctor of Philosophy
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