Recent advances in statistical methodology applied to the Hjort liver index time series (1859-2012) and associated influential factors

TL;DR

This paper reviews recent statistical methods and applies them to analyze the long-term Hjort liver index time series of Atlantic cod, revealing insights into biological and environmental factors over 150 years.

Contribution

It introduces advanced statistical techniques for modeling and analyzing long-term biological time series, specifically applied to the historic Hjort liver index data.

Findings

Identification of long-term trends in cod liver quality

Insights into environmental influences like winter temperatures

Application of dynamic goodness-of-fit testing methods

Abstract

Certain recent advances in statistical methodology have promising potential for fruitful use in general biology and the fisheries sciences. This paper reviews and discusses some of the relevant themes, including accurate modelling via focused model selection techniques, dynamic goodness-of-fit testing of processes evolving over time, finding break points for phenomena experiencing changes, prediction uncertainty, and optimal combination of information across diverse sources via confidence distributions. The methods are illustrated for the Hjort liver quality index time series. Its roots lie in the classic Hjort (`Fluctuations in the Great Fisheries of Northern Europe, Viewed in the Light of Biological Research', 1914), where liver quality of the Atlantic cod {\it (Gadus morhua)} for 1880--1912 is reported on and studied, along with related factors, making it one of the first teleost time series ever published. Diligent work by Kjesbu et al. (`Making use of Johan Hjort's `unknown' legacy: reconstruction of a 150-year coastal time-series on northeast Arctic cod (Gadus morhua) liver data reveals long-term trends in energy allocation patterns', 2014), involving both archival and calibration efforts, have extended the series both backwards and forwards in time, to 1859--2012, yielding one of the longest time series of marine science. Our study offers a detailed examination of this series and how it relates to and interacts with associated factors, including Kola winter temperatures, length distribution parameters, cod mortality, and a certain index related to availability of food.